Publications

2025

• Florian Bley, Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon
  Explaining Predictive Uncertainty by Exposing Second-Order Effects,
  Pattern Recognition, vol. 160, p. 111171, April 2025, doi: 10.1016/j.patcog.2024.111171, Open Access
• Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
  Explainable AI Reveals Clever Hans Effects in Unsupervised Learning Models,
  Nature Machine Intelligence, March 2025, doi: 10.1038/s42256-025-01000-2, Open Access
• Jesper Dramsch, Monique Kuglitsch, Miguel-Angel Fernandez-Torres, Andrea Toreti, Rustem Arif Albayrak, Lorenzo Nava, Saman Ghaffarian, Ximeng Cheng, Jackie Ma, Wojciech Samek, Rudy Venguswamy, Anirudh Koul, Raghavan Muthuregunathan, Arthur Hrast Essenfelder
  Explainability can foster trust in artificial intelligence in geoscience,
  Nature Geoscience, Springer Nature, ISSN: 1752-0908, vol. 18, no. 1, p. 3, February 2025, doi: 10.1038/s41561-025-01639-x
• Stephen Gilbert, Taras Holoyad, Rasmus Adler, Eva Weicken
  Could transparent model cards with layered accessible information drive trust and safety in health AI?,
  nature portfolio journal, February 2025, doi: https://doi.org/10.1038/s41746-025-01482-9, Open Access
• Karim Lekadir, Alejandro Frangi, Antonio Porras, Ben Glocker, Celia Cintas, Curtis Langlotz, Eva Weicken, Folkert Asselbergs, Fred Prior, Gary Collins, Georgios Kaissis, Gianna Tsakou, Irène Buvat, Jayashree Kalpathy-Cramer, John Mongan, Julia Schnabel, Kaisar Kushibar, Katrine Riklund, Kostas Marias, Lameck Amugongo, Lauren Fromont, Lena Maier-Hein, Leonor Cerdá-Alberich, Luis Martí-Bonmatí, M. Jorge Cardoso, Maciej Bobowicz, Mahsa Shabani, Manolis Tsiknakis, Maria Zuluaga, Marie-Christine Fritzsche, Marina Camacho, Marius George Linguraru, Markus Wenzel, Marleen De Bruijne, Martin Tolsgaard, Melanie Goisauf, Mónica Cano Abadía, Nikolaos Papanikolaou, Noussair Lazrak, Oriol Pujol, Richard Osuala, Sandy Napel, Sara Colantonio, Smriti Joshi, Stefan Klein, Susanna Aussó, Wendy Rogers, Zohaib Salahuddin, Martijn Starmans
  FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare,
  BMJ, BMJ Publishing Group Ltd, vol. 388, p. e081554, February 2025, doi: 10.1136/bmj-2024-081554, Open Access
• Anna Hedström, Philine Lou Bommer, Thomas F Burns, Sebastian Lapuschkin, Wojciech Samek, Marina M.-C. Höhne
  Explanation Faithfulness is Alignment: A Unifying and Geometric Perspective on Interpretability Evaluation,
  Transactions on Machine Learning Research, January 2025, Open Access
• Muhammad Asif, Monique Kuglitsch, Ivanka Pelivan, Raffaele Albano
  Review and Intercomparison of Machine Learning Applications for Short-term Flood Forecasting,
  Water Resources Management, Springer Nature, ISSN: 1573-1650, p. 21, January 2025, doi: 10.1007/s11269-025-04093-x, Open Access

2024

• Bernhard Föllmer, Sotirios Tsogias, Federico Biavati, Kenrick Schulze, Maria Bosserdt, Lars Gerrit Hövermann, Sebastian Stober, Wojciech Samek, Klaus F. Kofoed, Pál Maurovich-Horvat, Patrick Donnelly, Theodora Benedek, Michelle C. Williams, Marc Dewey
  Automated segment-level coronary artery calcium scoring on non-contrast CT: a multi-task deep-learning approach,
  Insights into Imaging, vol. 15, p. 250, October 2024, doi: 10.1186/s13244-024-01827-0
• Monique Kuglitsch, Jon Cox, Jürg Luterbacher, Bilel Jamoussi, Elena Xoplaki, Muralee Thummarukudy, Golestan Sally Radwan, Soichiro Yasukawa, Shanna N. McClain, Arif Albayrak, David Oehmen, Thomas Ward
  AI to the rescue: how to enhance disaster early warnings with tech tools,
  Nature, Springer Nature Limited, ISSN: 1476-4687, vol. 634, pp. 27-29, October 2024, doi: 10.1038/d41586-024-03149-z, Open Access
• Monique Kuglitsch, Ivanka Pelivan, Chinnawat Danakkaew, Jesper Dramsch, Reza Arghandeh
  Cultivating Trust in AI for Disaster Management,
  EOS, American Geophysical Union, ISSN: 2324-9250, vol. 105, no. 9, September 2024, doi: 10.1029/2024EO240402, Open Access
• Matthias I Gröschel, Francy J. Pérez-Llanos, Roland Diel, Roger Vargas Jr, Vincent Escuyer, Kimberlee Musser, Lisa Trieu, Jeanne Sullivan Meissner, Jillian Knorr, Peter Kouw, Susanne Homolka, Wojciech Samek, Barun Mathema, Dick van Soolingen, Stefan Niemann, Shama Ahuja, Maha R Farhat
  Differential Rates of Mycobacterium Tuberculosis Transmission Associate with Host–Pathogen Sympatry,
  Nature Microbiology, vol. 9, pp. 2113–2127, August 2024, doi: 10.1038/s41564-024-01758-y, Open Access
• Stefan Blücher, Johanna Vielhaben, Nils Strodthoff
  Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks,
  Transactions on Machine Learning Research, ISSN: @article{ bluecher2024decoupling, title={Decouplin, July 2024, arXiv: https://arxiv.org/abs/2401.06654, Open Access
• Philine Lou Bommer, Marlene Kretschmer, Anna Hedström, Dilyara Bareeva, Marina M.-C. Höhne
  Finding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science,
  Cover Artificial Intelligence for the Earth Systems Artificial Intelligence for the Earth Systems, July 2024, doi: https://doi.org/10.1175/AIES-D-23-0074.1, arXiv: https://arxiv.org/abs/2303.00652, Open Access
• Leon Witt, Usama Zafar, KuoYeh Shen, Felix Sattler, Dan Li, Wojciech Samek
  Decentralized and Incentivized Federated Learning: A Blockchain-Enabled Framework Utilising Compressed Soft-Labels and Peer Consistency,
  IEEE Transactions on Services Computing, vol. 17, no. 4, pp. 1449-1464, July 2024, doi: 10.1109/TSC.2023.3336980, Open Access
• Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf
  Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions,
  Information Fusion, vol. 106, p. 102301, June 2024, doi: 10.1016/j.inffus.2024.102301, Open Access
• Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek
  Explainable AI for Time Series via Virtual Inspection Layers,
  Pattern Recognition, vol. 150, p. 110309, June 2024, doi: doi.org/10.1016/j.patcog.2024.110309, Open Access
• Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William A Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha Noy, Vijay Janapa Reddi, James Zou, Praveen Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
  DMLR: Data-centric Machine Learning Research -- Past, Present and Future,
  Journal of Data-centric Machine Learning Research, April 2024, Open Access
• Clare A Primiero, Brigid Betz-Stablein, Nathan Ascott, Brian D'Alessandro, Seraphin Gaborit, Paul Fricker, Abigail Goldsteen, Sandra Gonzalez-Villa, Katie Lee, Sana Nazari, Hang Nguyen, Valsamis Ntsoukos, Frederik Pahde, Balazs E. Pataki, Josep Quintana, Susana Puig, Gisele G. Rezze, Rafael Garcia, H. Peter Soyer, Josep Malvehy
  A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification,
  Frontiers in Medicine, Frontiers, ISSN: 2296-858X, vol. 11, pp. 01-14, April 2024, doi: https://doi.org/10.3389/fmed.2024.1380984, Open Access
• Jacob R. Kauffmann, Malte Esders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
  From Clustering to Cluster Explanations via Neural Networks,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1926-1940, February 2024, doi: 10.1109/TNNLS.2022.3185901, Open Access
• Sören Becker, Johanna Vielhaben, Marcel Ackermann, Klaus-Robert Müller, Sebastian Lapuschkin, Wojciech Samek
  AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark,
  Journal of the Franklin Institute, Elsevier, ISSN: 0016-0032, vol. 361, no. 1, pp. 418-428, January 2024, doi: 10.1016/j.jfranklin.2023.11.038, Open Access
• Markus Wenzel, Erik Grüner, Nils Strodthoff
  Insights into the inner workings of transformer models for protein function prediction,
  Bioinformatics, Oxford University Press, ISSN: 1367-4811, p. btae031, January 2024, doi: 10.1093/bioinformatics/btae031, Open Access
• Andreas Rieckmann, Sebastian Nielsen, Piotr Dworzynski, Heresh Amini, Søren Wengel Mogensen, Isaquel Bartolomeu Silva, Angela Yuwen Chang, Onyebuchi A. Arah, Wojciech Samek, Naja H. Rod, Claus T. Ekstrom, Christine Stabell Benn, Peter Aaby, Ane Bærent Fisker
  Discovering Sub-Groups of Children with High Mortality in Urban Guinea-Bissau : An Exploratory and Validation Cohort Study,
  JMIR Public Health and Surveillance, vol. 10, p. e48060, January 2024, doi: 10.2196/48060, Open Access
• Daniel Becking, Karsten Müller, Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  Neural Network Coding of Difference Updates for Efficient Distributed Learning Communication,
  IEEE Transactions on Multimedia, vol. 26, pp. 6848-6863, January 2024, doi: 10.1109/TMM.2024.3357198, Open Access
• Nakul Prasad, Stefan Uhlenbrook, Hwirin Kim, Celine Cattoen, William Scharffenberg, Monique Kuglitsch, Abd Salam El Vilaly, Bilel Jamoussi
  Bridging virtual and physical realms: leveraging immersive technologies for water and land management,
  United in Science, World Meteorological Organization, no. 2024, p. 48, 2024, Open Access
• Florian Pappenberger, Nils Wedi, Matthew Chantry, Christian Lessig, Simon Lang, Peter Dueben, Mariana Clare, Linus Magnusson, Estíbaliz Gascón, Florence Rabier, Amy McGovern, Hèou Maléki Badjana, Catherine de Burgh-Day, Jürg Luterbacher, Monique Kuglitsch, Hannah L. Cloke
  Artificial intelligence and machine learning: revolutionizing weather forecasting,
  United in Science, World Meteorological Organization, no. 2024, p. 48, 2024, Open Access

2023

• David Neumann, Andreas Lutz, Karsten Müller, Wojciech Samek
  A Privacy Preserving System for Movie Recommendations using Federated Learning,
  ACM Transactions on Recommender Systems, November 2023, doi: 10.1145/3634686
• Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima
  Langevin Cooling for Unsupervised Domain Translation,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 10, pp. 7675-7688, October 2023, doi: 10.1109/TNNLS.2022.3145812, Open Access
• Jose Albites-Sanabria, Barry R Greene, Killian McManus, Luca Palmerini, Pierpaolo Palumbo, Inês Sousa, Kimberley S van Schooten, Eva Weicken, Markus Wenzel
  Fall risk stratification of community-living older people. Commentary on the world guidelines for fall prevention and management,
  Age and Ageing, ISSN: 1468-2834, vol. 52, no. 10, p. afad162, October 2023, doi: https://doi.org/10.1093/ageing/afad162, Open Access
• Felix Sattler, Tim Korjakow, Roman Rischke, Wojciech Samek
  FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 9, pp. 5531-5543, September 2023, doi: 10.1109/TNNLS.2021.3129371, Open Access
• Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
  From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation,
  Nature Machine Intelligence, Nature Publishing Group, ISSN: 2522-5839, vol. 5, no. 9, pp. 1006-1019, September 2023, doi: 10.1038/s42256-023-00711-8, Open Access
• Monique Kuglitsch, Arif Albayrak, Jürg Lüterbacher, Allison Craddock, Andrea Toreti, Jackie Ma, Paula Padrino Vilela, Elena Xoplaki, Rui Kotani, Dominique Berod, Jon Cox
  When it comes to Earth observations in AI for disaster risk reduction, is it feast or famine? A topical review,
  Environmental Research Letters, vol. 18, no. 9, September 2023, doi: https://doi.org/10.1088/1748-9326/acf601, Open Access
• Anna Hedström, Philine Bommer, Kristoffer K. Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne
  The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus,
  Transactions on Machine Learning Research, ISSN: 2835-8856, July 2023, doi: https://openreview.net/forum?id=j3FK00HyfU, Open Access
• Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller
  Evaluating deep transfer learning for whole-brain cognitive decoding,
  Journal of the Franklin Institute, vol. 360, no. 13, pp. 9754-9787, July 2023, doi: 10.1016/j.jfranklin.2023.07.015
• Sara Mirzavand Borujeni, Leila Arras, Vignesh Srinivasan, Wojciech Samek
  Explainable Sequence-to-Sequence GRU Neural Network for Pollution Forecasting,
  Scientific Reports, vol. 13, no. 9940, June 2023, doi: 10.1038/s41598-023-35963-2, Open Access
• Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti
  Data Models for Dataset Drift Controls in Machine Learning With Optical Images,
  Transactions on Machine Learning Research, ISSN: 2835-8856, May 2023, doi: https://openreview.net/forum?id=I4IkGmgFJz, Open Access
• Patrick Wagner, Maximilian Springenberg, Marius Kröger, Rose K. C. Moritz, Johannes Schleusener, Martina C. Meinke, Jackie Ma
  Semantic modeling of cell damage prediction: A machine learning approach at human-level performance in dermatology,
  Nature Scientific Reports, May 2023, doi: 10.1038/s41598-023-35370-7, Open Access
• Maximilian Springenberg, Annika Frommholz, Markus Wenzel, Eva Weicken, Jackie Ma, Nils Strodthoff
  From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology,
  Medical Image Analysis, Elsevier, ISSN: 1361-8415, April 2023, doi: 10.1016/j.media.2023.102809, arXiv: https://arxiv.org/abs/2204.05044
• Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek
  Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement,
  Information Fusion, vol. 92, pp. 154-176, April 2023, doi: 10.1016/j.inffus.2022.11.013, Open Access
• Saul Calderon-Ramirez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, Armaghan Moemeni, Wojciech Samek, Miguel A. Molina-Cabello
  Dataset Similarity to Assess Semi-supervised Learning Under Distribution Mismatch Between the Labelled and Unlabelled Datasets,
  IEEE Transactions on Artificial Intelligence, vol. 4, no. 2, pp. 282-291, April 2023, doi: 10.1109/TAI.2022.3168804, Open Access
• Andrew Farlow, Alexander Hofmann, Girmaw Abebe Tadesse, Deogratias Mzurikwao, Rob Beyer, Darlington Akogo, Eva Weicken, Tafadzwa Matika, MaryJane Ijeoma Nweje, Watu Wamae, Sako Arts, Thomas Wiegand, Colin Bennett, Maha R. Farhat, Matthias I. Gröschel
  Rethinking global digital health and AI-for-health innovation challenges,
  PLOS Global Public Health, Public Library of Science, ISSN: 2767-3375, vol. 3, no. 4, pp. 1-12, April 2023, doi: 10.1371/journal.pgph.0001844, Open Access
• Michele Gazzea, Amir Miraki, Onur Alisan, Monique Kuglitsch, Ivanka Pelivan, Eren Erman Ozguven, Reza Arghandeh
  Traffic monitoring system design considering multi-hazard disaster risks,
  Nature Scientific Reports, March 2023, Open Access
• Alexander Henry Thieme, Yuanning Zheng, Gautam Machiraju, Chris Sadee, Mirja Mittermaier, Maximilian Gertler, Jorge L. Salinas, Krithika Srinivasan, Prashnna Gyawali, Francisco Carrillo-Perez, Angelo Capodici, Maximilian Uhlig, Daniel Habenicht, Anastassia Löser, Maja Kohler, Maximilian Schuessler, David Kaul, Johannes Gollrad, Jackie Ma, Christoph Lippert, Kendall Billick, Isaac Bogoch, Tina Hernandez-Boussard, Pascal Geldsetzer, Olivier Gevaert
  A deep-learning algorithm to classify skin lesions from mpox virus infection,
  Nature Medicine, March 2023, Open Access
• Leon Witt, Mathis Heyer, Kentaroh Toyoda, Wojciech Samek, Dan Li
  Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review,
  IEEE Internet of Things Journal, vol. 10, no. 4, pp. 3642-3663, February 2023, doi: 10.1109/JIOT.2022.3231363, Open Access
• Anna Hedström, Leander Weber, Daniel Krakowczyk, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne
  Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond,
  Journal of Machine Learning Research, vol. 24, no. 34, pp. 1-11, January 2023, arXiv: https://jmlr.org/papers/v24/22-0142.html, Open Access
• Martin-Leo Hansmann, Frederick Klauschen, Wojciech Samek, Klaus-Robert Müller, Emmanuel Donnadieu, Sonja Scharf, Sylvia Hartmann, Ina Koch, Jörg Ackermann, Liron Pantanowitz, Hendrik Schäfer, Patrick Wurzel
  Imaging bridges pathology and radiology?,
  Journal of Pathology Informatics, vol. 14, p. 100298, January 2023, doi: 10.1016/j.jpi.2023.100298
• Gayathri Venugopal, Karsten Müller, Jonathan Pfaff, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  Region-Based Template Matching Prediction for Intra Coding,
  IEEE Transactions on Image Processing, vol. 32, no. 1, pp. 779-790, January 2023, doi: 10.1109/TIP.2022.3233184, Open Access

2022

• Simon M. Hofmann, Frauke Beyer, Sebastian Lapuschkin, Ole Goltermann, Markus Loeffler, Klaus-Robert Müller, Arno Villringer, Wojciech Samek, A. Veronica Witte
  Towards the Interpretability of Deep Learning Models for Multi-Modal Neuroimaging: Finding Structural Changes of the Ageing Brain,
  NeuroImage, vol. 261, p. 119504, November 2022, doi: 10.1016/j.neuroimage.2022.119504, Open Access
• Patrick Wagner, Nils Strodthoff, Patrick Wurzel, Arturo Marban, Sonja Scharf, Hendrik Schäfer, Philipp Seegerer, Andreas Loth, Sylvia Hartmann, Frederick Klauschen, Klaus-Robert Müller, Wojciech Samek, Martin-Leo Hansmann
  New Definitions of Human Lymphoid and Follicular Cell Entities in Lymphatic Tissue by Machine Learning,
  Scientific Reports, vol. 12, p. 18991, November 2022, doi: 10.1038/s41598-022-18097-9, Open Access
• Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek
  To Pretrain or Not? A Systematic Analysis of the Benefits of Pretraining in Diabetic Retinopathy,
  PLoS ONE, vol. 17, no. 10, p. e0274291, October 2022, doi: 10.1371/journal.pone.0274291, Open Access
• Wojciech Samek
  Von der Blackbox zur erklärbaren und vertrauenswürdigen KI,
  Quintessenz Zahnmedizin, vol. 73, no. 9, pp. 868-873, September 2022
• Roman Rischke, Lisa Schneider, Karsten Müller, Wojciech Samek, Falk Schwendicke, Joachim Krois
  Federated Learning in Dentistry: Chances and Challenges,
  Journal of Dental Research, vol. 101, no. 11, pp. 1269-1273, July 2022, doi: 10.1177/00220345221108953
• Jackie Ma, Lisa Schneider, Sebastian Lapuschkin, Reduan Achtibat, Martha Duchrau, Joachim Krois, Falk Schwendicke, Wojciech Samek
  Towards Trustworthy AI in Dentistry,
  Journal of Dental Research, vol. 101, no. 11, pp. 1263-1268, June 2022, doi: 10.1177/00220345221106086
• Felix Sattler, Arturo Marban, Roman Rischke, Wojciech Samek
  CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding,
  IEEE Transactions on Network Science and Engineering, vol. 9, no. 4, pp. 2025-2038, June 2022, doi: 10.1109/TNSE.2021.3081748, Open Access
• Leila Arras, Ahmed Osman, Wojciech Samek
  CLEVR-XAI: A Benchmark Dataset for the Ground Truth Evaluation of Neural Network Explanations,
  Information Fusion, vol. 81, pp. 14-40, May 2022, doi: 10.1016/j.inffus.2021.11.008, Open Access
• Ximeng Cheng, Ali Doosthosseini, Julian Kunkel
  Improve the Deep Learning Models in Forestry Based on Explanations and Expertise,
  Frontiers in Plant Science, ISSN: 1664-462X, vol. 13, p. 902105, May 2022, doi: 10.3389/fpls.2022.902105, Open Access
• Heiner Kirchhoffer, Paul Haase, Wojciech Samek, Karsten Müller, Hamed Rezazadegan-Tavakoli, Francesco Cricri, Emre Aksu, Miska M. Hannuksela, Wei Jiang, Wei Wang, Shan Liu, Swayambhoo Jain, Shahab Hamidi-Rad, Fabien Racape, Werner Bailer
  Overview of the Neural Network Compression and Representation (NNR) Standard,
  IEEE Transactions on Circuits and Systems for Video Technology, IEEE, vol. 32, no. 5, pp. 3203-3216, May 2022, doi: 10.1109/TCSVT.2021.3095970, Open Access
• Andreas Rieckmann, Piotr Dworzynski, Leila Arras, Sebastian Lapuschkin, Wojciech Samek, Onyebuchi A. Arah, Naja H. Rod, Claus T. Ekstrom
  Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome,
  International Journal of Epidemiology, vol. 51, no. 5, pp. 1622–1636, May 2022, doi: 10.1093/ije/dyac078, Open Access
• Bernhard Föllmer, Federico Biavati, Christian Wald, Sebastian Stober, Marc Dewey, Jackie Ma, Wojciech Samek
  Active Multi-Task Learning with Uncertainty Weighted Loss for Coronary Calcium Scoring,
  Medical Physics, vol. 49, no. 11, pp. 7262-7277, May 2022, doi: 10.1002/mp.15870
• Djordje Slijepcevic, Fabian Horst, Sebastian Lapuschkin, Brian Horsak, Anna-Maria Raberger, Andreas Kranzl, Wojciech Samek, Christian Breiteneder, Wolfgang I. Schöllhorn, Matthias Zeppelzauer
  Explaining Machine Learning Models for Clinical Gait Analysis,
  ACM Transactions on Computing for Healthcare, ACM Digital Library, ISSN: 2691-1957, vol. 3, no. 2, pp. 1-27, April 2022, doi: 10.1145/3505188, Open Access
• Andreas Holzinger, Matthias Dehmer, Frank Emmert-Streib, Natalia Diaz-Rodriguez, Rita Cucchiara, Isabelle Augenstein, Javier Del Ser, Wojciech Samek, Igor Jurisica
  Information Fusion as an Integrative Cross-Cutting Enabler to Achieve Robust, Explainable, and Trustworthy Medical Artificial Intelligence,
  Information Fusion, vol. 79, pp. 263-278, March 2022, doi: 10.1016/j.inffus.2021.10.007, Open Access
• Monique Kuglitsch, Arif Albayrak, Raúl Aquino, Allison Craddock, Jaselle Edward-Gill, Rinku Kanwar, Anirudh Koul, Jackie Ma, Alejandro Marti, Mythili Menon, Ivanka Pelivan, Andrea Toreti, Rudy Venguswamy, Tom Ward, Elena Xoplaki, Anthony Rea, Jürg Lüterbacher
  Artificial Intelligence for Disaster Risk Reduction: Opportunities, challenges, and prospects,
  WMO Bulletin, March 2022, Open Access
• Monique Kuglitsch, Ivanka Pelivan, Serena Ceola, Mythili Menon, Elena Xoplaki
  Facilitating adoption of AI in natural disaster management through collaboration,
  Nature Communications, March 2022, doi: https://doi.org/10.1038/s41467-022-29285-6, Open Access
• Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
  Toward Explainable AI for Regression Models,
  IEEE Signal Processing Magazine, vol. 39, no. 4, pp. 40-58, February 2022, doi: 10.1109/MSP.2022.3153277, Open Access
• Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder
  Explain and Improve: LRP-Inference Fine Tuning for Image Captioning Models,
  Information Fusion, vol. 77, pp. 233-246, January 2022, doi: 10.1016/j.inffus.2021.07.008, Open Access
• Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
  Finding and Removing Clever Hans: Using Explanation Methods to Debug and Improve Deep Models,
  Information Fusion, vol. 77, pp. 261-295, January 2022, doi: 10.1016/j.inffus.2021.07.015, Open Access

2021

• Luis Oala, Andrew G. Murchison, Pradeep Balachandran, Shruti Choudhary, Jana Fehr, Alixandro Werneck Leite, Peter G. Goldschmidt, Christian Johner, Elora D. M. Schörverth, Rose Nakasi, Martin Meyer, Federico Cabitza, Pat Baird, Carolin Prabhu, Eva Weicken, Xiaoxuan Liu, Markus Wenzel, Steffen Vogler, Darlington Akogo, Shada Alsalamah, Emre Kazim, Adriano Koshiyama, Sven Piechottka, Sheena Macpherson, Ian Shadforth, Regina Geierhofer, Christian Matek, Joachim Krois, Bruno Sanguinetti, Matthew Arentz, Pavol Bielik, Saul Calderon-Ramirez, Auss Abbood, Nicolas Langer, Stefan Haufe, Ferath Kherif, Sameer Pujari, Wojciech Samek, Thomas Wiegand
  Machine Learning for Health: Algorithm Auditing & Quality Control,
  Journal of Medical Systems, vol. 45, p. 105, October 2021, doi: 10.1007/s10916-021-01783-y
• Sandeep Reddy, Wendy Rogers, Ville-Petteri Makinen, Enrico Coeira, Pieta Brown, Markus Wenzel, Eva Weicken, Saba Ansari, Piyush Mathur, Aaron Casey, Blair Kelly
  Evaluation framework to guide implementation of AI systems into healthcare settings,
  BMJ Health & Care Informatics , BMJ, vol. 28, no. 1, p. e100444, October 2021, doi: 10.1136/bmjhci-2021-100444, Open Access
• Karsten Müller, Wojciech Samek, Detlev Marpe
  Ein internationaler KI-Standard zur Kompression Neuronaler Netze,
  FKT- Fachzeitschrift für Fernsehen, Film und Elektronische Medien, pp. 33-36, September 2021
• Luis Oala, Cosmas Heiß, Jan Macdonald, Maximilian März, Gitta Kutyniok, Wojciech Samek
  Detecting Failure Modes in Image Reconstructions with Interval Neural Network Uncertainty,
  International Journal of Computer Assisted Radiology and Surgery, vol. 16, pp. 2089-2097, August 2021, doi: 10.1007/s11548-021-02482-2
• Felix Sattler, Klaus-Robert Müller, Wojciech Samek
  Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 8, pp. 3710-3722, August 2021, doi: 10.1109/TNNLS.2020.3015958, Open Access
• Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Alexander Binder, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
  Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning,
  Pattern Recognition, vol. 115, p. 107899, July 2021, doi: 10.1016/j.patcog.2021.107899, Open Access
• Till M. Schneider, Jackie Ma, Patrick Wagner, Nicolas Behl, Armin Michael Nagel, Mark E. Ladd, Sabine Heiland, Martin Bendszus, Sina Straub
  Multiparametric MRI for characterization of the basal ganglia and the midbrain,
  Frontiers in Neuroscience, June 2021, doi: 10.3389/fnins.2021.661504, Open Access
• Nils Strodthoff, Patrick Wagner, Tobias Schaeffter, Wojciech Samek
  Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL,
  IEEE Journal of Biomedical And Health Informatics, vol. 25, no. 5, pp. 1519-1528, May 2021, doi: 10.1109/JBHI.2020.3022989, Open Access
• Simon Wiedemann, Suhas Shivapakashy, Pablo Wiedemann, Daniel Becking, Wojciech Samek, Friedel Gerfers, Thomas Wiegand
  FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons,
  IEEE Open Journal of Circuits and Systems, vol. 2, pp. 407-419, May 2021, doi: 10.1109/OJCAS.2021.3083332, Open Access
• Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
  Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications,
  Proceedings of the IEEE, vol. 109, no. 3, pp. 247-278, March 2021, doi: 10.1109/JPROC.2021.3060483, Open Access
• Nils Strodthoff, Claas Strodthoff, Tobias Becher, Inéz Frerichs, Norbert Weiler
  Inferring respiratory and circulatory parameters from electrical impedance tomography with deep recurrent models,
  IEEE Journal of Biomedical and Health Informatics, February 2021, doi: 10.1109/JBHI.2021.3059016, arXiv: https://arxiv.org/abs/2010.09622, Open Access
• Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
  A Unifying Review of Deep and Shallow Anomaly Detection,
  Proceedings of the IEEE, vol. 109, no. 5, pp. 756-795, February 2021, doi: 10.1109/JPROC.2021.3052449
• Vignesh Srinivasan, Arturo Marban, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima
  Robustifying Models Against Adversarial Attacks by Langevin Dynamics,
  Neural Networks, vol. 137, pp. 1-17, January 2021, doi: 10.1016/j.neunet.2020.12.024
• Jeroen Aeles, Fabian Horst, Sebastian Lapuschkin, Lilian Lacourpaille, François Hug
  Revealing the unique features of each individual's muscle activation signatures,
  Journal Of The Royal Society Interface, The Royal Society, ISSN: 1742-5662, vol. 18, no. 174, p. 20200770, January 2021, doi: https://doi.org/10.1098/rsif.2020.0770, Open Access

2020

• Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand
  Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements,
  Nature Digital Medicine, September 2020, doi: 10.1038/s41746-020-00340-0, Open Access
• Markus Wenzel, Thomas Wiegand
  Toward Global Validation Standards for Health AI,
  IEEE Communications Standards Magazine , IEEE, ISSN: 2471-2833, vol. 4, no. 3, pp. 64-69, September 2020, doi: https://doi.org/10.1109/MCOMSTD.001.2000006, Invited Paper
• Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
  Robust and Communication-Efficient Federated Learning from Non-IID Data,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3400-3413, September 2020, doi: 10.1109/TNNLS.2019.2944481, Open Access
• Fabian Horst, Djordje Slijepcevic, Matthias Zeppelzauer, Anna-Maria Raberger, Sebastian Lapuschkin, Wojciech Samek, Wolfgang I. Schöllhorn, Christian Breiteneder, Brian Horsak
  Explaining automated gender classification of human gait,
  Gait & Posture, Elsevier, ISSN: 0966-6362, vol. 81, pp. 159-160, September 2020, doi: https://doi.org/10.1016/j.gaitpost.2020.07.114
• Clemens Peter Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert
  Accurate and Robust Neural Networks for Face Morphing Attack Detection,
  Journal of Information Security and Applications, vol. 53, p. 102526, August 2020, doi: 10.1016/j.jisa.2020.102526, arXiv: https://arxiv.org/abs/1806.04265
• Johanna Vielhaben, Markus Wenzel, Wojciech Samek, Nils Strodthoff
  USMPep: Universal Sequence Models for Major Histocompatibility Complex Binding Affinity Prediction,
  BMC Bioinformatics, vol. 21, p. 279, July 2020, doi: 10.1186/s12859-020-03631-1, Open Access
• Falk Schwendicke, Wojciech Samek, Joachim Krois
  Artificial Intelligence in Dentistry: Chances and Challenges,
  Journal of Dental Research, vol. 99, no. 7, pp. 769-774, July 2020, doi: 10.1177/0022034520915714
• Felix Sattler, Thomas Wiegand, Wojciech Samek
  Trends and Advancements in Deep Neural Network Communication,
  ITU Journal: ICT Discoveries, vol. 3, no. 1, May 2020
• Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, David Neumann, Tung Nguyen, Ahmed Osman, Heiko Schwarz, Detlev Marpe, Thomas Wiegand, Wojciech Samek
  DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks,
  IEEE Journal of Selected Topics in Signal Processing, vol. 14, no. 4, pp. 700-714, May 2020, doi: 10.1109/JSTSP.2020.2969554
• Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
  Compact and Computationally Efficient Representation of Deep Neural Networks,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 3, pp. 772-785, May 2020, doi: 10.1109/TNNLS.2019.2910073
• Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Dieter Kreiseler, Fatima I. Lunze, Wojciech Samek, Tobias Schaeffter
  PTB-XL, A Large Publicly Available Electrocardiography Dataset,
  Scientific Data, vol. 7, p. 154, May 2020, doi: 10.1038/s41597-020-0495-6, Open Access
• Stefan Blücher, Lukas Kades, Jan M. Pawlowski, Nils Strodthoff, Julian M. Urban
  Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning,
  Phys. Rev. D, vol. 101, no. 094507, May 2020, doi: 10.1103/PhysRevD.101.094507, arXiv: https://arxiv.org/abs/2003.01504
• Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, Alexander Binder
  Resolving Challanges in Deep Learning-Based Analyses of Histopathological Images using Explanation Methods,
  Scientific Reports, Nature Research, Springer Nature, vol. 10, p. 6423, April 2020, doi: 10.1038/s41598-020-62724-2, Open Access
• Kim A. Nicoli, Shinichi Nakajima, Nils Strodthoff, Wojciech Samek, Klaus-Robert Müller, Pan Kessel
  Asymptotically Unbiased Estimation of Physical Observables with Neural Samplers,
  Physical Review E, vol. 101, no. 2, p. 023304, February 2020, doi: 10.1103/PhysRevE.101.023304
• Wojciech Samek
  Learning with Explainable Trees,
  Nature Machine Intelligence, Springer Nature Limited, ISSN: 2522-5839, vol. 2, pp. 16-17, January 2020, doi: 10.1038/s42256-019-0142-0
• Nils Strodthoff, Patrick Wagner, Markus Wenzel, Wojciech Samek
  UDSMProt: Universal Deep Sequence Models for Protein Classification,
  Bioinformatics, btaa003, Oxford University Press, vol. 36, no. 8, pp. 2401-2409, January 2020, doi: 10.1093/bioinformatics/btaa003

2019

• Armin W. Thomas, Hauke R. Heekeren, Klaus-Robert Müller, Wojciech Samek
  Analyzing Neuroimaging Data Through Recurrent Deep Learning Models,
  Frontiers in Neuroscience, vol. 13, p. 1321, December 2019, doi: 10.3389/fnins.2019.01321
• Nils Strodthoff, Baris Göktepe, Thomas Schierl, Cornelius Hellge, Wojciech Samek
  Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G,
  IEEE Journal on Selected Areas in Communications, vol. 37, no. 11, pp. 2573-2587, August 2019, doi: 10.1109/JSAC.2019.2934001
• Sebastian Bosse, Sören Becker, Klaus-Robert Müller, Wojciech Samek, Thomas Wiegand
  Estimation of Distortion Sensitivity for Visual Quality Prediction Using a Convolutional Neural Network,
  Digital Signal Processing, Elsevier B.V., vol. 91, pp. 54-65, August 2019, doi: 10.1016/j.dsp.2018.12.005
• Ahmed Osman, Wojciech Samek
  DRAU: Dual Recurrent Attention Units for Visual Question Answering,
  Computer Vision and Image Understanding, Elsevier Ltd., vol. 185, pp. 24-30, August 2019, doi: 10.1016/j.cviu.2019.05.001
• Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
  iNNvestigate neural networks!,
  Journal of Machine Learning Research, vol. 20, no. 93, pp. 1-8, June 2019, Download: http://jmlr.org/papers/v20/18-540.html
• Tatiana. A. Bubba, Gitta Kutyniok, Matti Lassas, Maximilian März, Wojciech Samek, Samuli Siltanen, Vignesh Srinivasan
  Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography,
  Journal of Inverse Problems, IOP Publishing, vol. 35, no. 6, p. 064002, May 2019, doi: 10.1088/1361-6420/ab10ca
• Arturo Marban, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals
  A Recurrent Convolutional Neural Network Approach for Sensorless Force Estimation in Robotic Surgery,
  Biomedical Signal Processing and Control, Elsevier, ISSN: 1746-8094, vol. 50, pp. 134-150, April 2019, doi: 10.1016/j.bspc.2019.01.011
• Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
  Unmasking Clever Hans Predictors and Assessing What Machines Really Learn,
  Nature Communications, Nature Research, vol. 10, p. 1096, March 2019, doi: 10.1038/s41467-019-08987-4, Open Access
• Fabian Horst, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller, Wolfgang I. Schöllhorn
  Explaining the Unique Nature of Individual Gait Patterns with Deep Learning,
  Scientific Reports, Nature Research, Springer Nature, vol. 9, p. 2391, February 2019, doi: 10.1038/s41598-019-38748-8
• Nils Strodthoff, Claas Strodthoff
  Detecting and interpreting myocardial infarction using fully convolutional neural networks,
  Physiological Measurement, IOPscience, IOP Publishing, vol. 40, no. 1, p. 015001, January 2019, doi: 10.1088/1361-6579/aaf34d

2018

• Stephan Kaltenstadler, Shinichi Nakajima, Klaus-Robert Müller, Wojciech Samek
  Wasserstein Stationary Subspace Analysis,
  Journal of Selected Topics in Signal Processing, IEEE, vol. 12, no. 6, pp. 1213-1223, December 2018, doi: 10.1109/JSTSP.2018.2873987
• Sebastian Bosse, Laura Acqualagna, Wojciech Samek, Anne K. Porbadnigk, Gabriel Curio, Benjamin Blankertz, Klaus-Robert Müller, Thomas Wiegand
  Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition,
  IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 8, pp. 1694-1706, August 2018, doi: 10.1109/tcsvt.2017.2694807
• Forooz Shahbazi Avarvand, Sarah Bartz, Christina Andreou, Wojciech Samek, Gregor Leicht, Christoph Mulert, Guido Nolte, Andreas Karl Engel, System Import
  Localizing Bicoherence from EEG and MEG,
  NeuroImage, Elsevier Inc., vol. 174, pp. 352-363, July 2018, doi: 10.1016/j.neuroimage.2018.01.044
• Wiktor Pronobis, Danny Panknin, Johannes Kirschnick, Vignesh Srinivasan, Wojciech Samek, Volker Markl, Manohar Kaul, Klaus-Robert Müller, Shinichi Nakajima
  Sharing Hash Codes for Multiple Purposes,
  Japanese Journal of Statistics and Data Science (JJSD), Springer Verlag, vol. 1, no. 1, pp. 215–246, June 2018, doi: 10.1007/s42081-018-0010-x
• Wojciech Samek, Thomas Wiegand, Klaus-Robert Müller
  Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models,
  ITU Journal: ICT Discoveries - Special Issue 1 - The Impact of Artificial Intelligence (AI) on Communication Networks and Services, vol. 1, no. 1, pp. 39-48, March 2018, Invited Paper, Special Issue
• Wojciech Samek, Slawomir Stanczak, Thomas Wiegand
  The Convergence of Machine Learning and Communications,
  ITU Journal: ICT Discoveries - Special Issue 1 - The Impact of Artificial Intelligence (AI) on Communication Networks and Services, vol. 1, no. 1, pp. 49-58, March 2018, Invited Paper, Special Issue
• Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
  Methods for Interpreting and Understanding Deep Neural Networks,
  Digital Signal Processing, Elsevier Inc., vol. 73, pp. 1-15, February 2018, doi: 10.1016/j.dsp.2017.10.011
• Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek
  Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment,
  IEEE Transactions on Image Processing, vol. 27, no. 1, pp. 206-219, January 2018, doi: 10.1109/tip.2017.2760518

2017

• Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller
  Evaluating the visualization of what a Deep Neural Network has learned,
  IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 11, pp. 2660-2673, November 2017, doi: 10.1109/tnnls.2016.2599820
• Wojciech Samek, Shinichi Nakajima, Motoaki Kawanabe, Klaus-Robert Müller
  On Robust Parameter Estimation in Brain-Computer Interfacing,
  Journal of Neural Engineering, IOP Publishing, vol. 14, no. 6, pp. 1-17, November 2017, doi: 10.1088/1741-2552/aa8232
• Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  "What is Relevant in a Text Document?": An Interpretable Machine Learning Approach,
  Open Access journal - PLOS ONE (Public Library of Science), Cambridge, vol. 12, no. 8, p. E0181142, August 2017, doi: 10.1371/journal.pone.0181142
• Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek, Klaus-Robert Müller
  Explaining Nonlinear Classification Decisions with Deep Taylor Decomposition,
  Pattern Recognition, Elsevier Inc., vol. 65, pp. 211–222, May 2017, doi: 10.1016/j.patcog.2016.11.008
• Forooz Shahbazi Avarvand, Sebastian Bosse, Klaus-Robert Müller, Guido Nolte, Thomas Wiegand, Ralf Schäfer, Gabriel Curio, Wojciech Samek
  Objective Quality Assessment of Stereoscopic Images with Vertical Disparity using EEG,
  Journal of Neural Engineering, IOP Publishing, vol. 14, no. 4, p. 046009, May 2017, doi: 10.1088/1741-2552/aa6d8b

2016

• Irene Sturm, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller
  Interpretable Deep Neural Networks for Single-Trial EEG Classification,
  Journal of Neuroscience Methods, Elsevier Inc., vol. 274, pp. 141-145, December 2016, doi: 10.1016/j.jneumeth.2016.10.008
• Wojciech Samek, Duncan Blythe, Gabriel Curio, Klaus-Robert Müller, Benjamin Blankertz, Vadim V. Nikulin
  Multiscale temporal neural dynamics predict performance in a complex sensorimotor task,
  NeuroImage, Elsevier Inc., vol. 141, pp. 291–303, November 2016, doi: 10.1016/j.neuroimage.2016.06.056
• G. Weber, O. Böpple, M. Weber, Paul Chojecki, Detlef Ruschin, K. Köppe, S. Glende, et al.
  DIN SPEC 91333:2016-08 (D): Berührungslose Gestensteuerung zur Mensch-System-Interaktion (Contactless gesture control for human-system interaction),
  Technische Regel DIN Spec No. 91333:2016-08 (D), Beuth Verlag, August 2016
• Stephanie Brandl, Laura Frølich, Johannes Höhne, Klaus-Robert Müller, Wojciech Samek
  Brain-Computer Interfacing under Distraction: An Evaluation Study,
  Journal of Neural Engineering, IOP Publishing, vol. 13, no. 5, p. 056012, August 2016, doi: 10.1088/1741-2560/13/5/056012
• Wojciech Samek
  On robust spatial filtering of EEG in nonstationary environments,
  it-Information Technology, Distinguished Dissertations, vol. 58, no. 3, pp. 150–154, June 2016, doi: 10.1515/itit-2016-0023
• Paul Chojecki, Detlef Ruschin, David Przewozny
  Let 's talk about Gestures! Ein Notationssystem zur Beschreibung räumlicher Gesten in der Entwicklung interaktiver Mensch-Technik-Systeme,
  Bullinger, A.C. (Hrsg.), 3D SENSATION - transdisziplinäre Perspektiven., Verlag aw&I Wissenschaft und Praxis, June 2016
• Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  The Layer-wise Relevance Propagation Toolbox for Artificial Neural Networks,
  Journal of Machine Learning Research, vol. 17, no. 114, pp. 1-5, January 2016

2015

• Sven Dähne, Felix Bießmann, Wojciech Samek, Stefan Haufe, Dominique Goltz, Christopher Gundlach, Arno Villringer, Siamac Fazli, Klaus-Robert Müller
  Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data,
  Proceedings of the IEEE, vol. 103, no. 9, pp. 1507-1530, September 2015, doi: 10.1109/jproc.2015.2425807, Invited Paper
• Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, Wojciech Samek
  On Pixel-wise Explanations for Non-Linear Classifier Decisions by Layer-wise Relevance Propagation,
  PLOS ONE, vol. 10, no. 7, p. e0130140, July 2015, doi: 10.1371/journal.pone.0130140, Open Access
• Siamac Fazli, Sven Dähne, Wojciech Samek, Felix Bießmann, Klaus-Robert Müller
  Learning from more than one Data Source: Data Fusion Techniques for Sensorimotor Rhythm-based Brain-Computer Interfaces,
  Proceedings of the IEEE, vol. 103, no. 6, pp. 891-906, June 2015, doi: 10.1109/jproc.2015.2413993, Invited Paper

2025

• Eren Erogullari, Sebastian Lapuschkin, Wojciech Samek, Frederik Pahde
  Post-Hoc Concept Disentanglement: From Correlated to Isolated Concept Representations,
  Explainable Artificial Intelligence, Third World Conference, xAI 2025, Istanbul, Turkey, Springer, Cham, July 2025
• Jonas Naujoks, Aleksander Krasowski, Moritz Weckbecker, Galip Ümit Yolcu, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek, René P. Klausen
  Leveraging Influence Functions for Resampling in PINNs,
  Explainable Artificial Intelligence, Third World Conference, xAI 2025, Istanbul, Turkey, Springer, Cham, June 2025
• Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker, Leander Weber, Christopher J. Anders, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
  Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence,
  International Conference on Learning Representations (ICLR), Singapore, April 2025
• Egor Zverev, Evgenii Kortukov, Alexander Panfilov, Soroush Tabesh, Sebastian Lapuschkin, Wojciech Samek, Christoph H. Lampert
  ASIDE: Architectural Separation of Instructions and Data in Language Models,
  ICLR 2025 Workshop on Building Trust in LLMs and LLM Applications: From Guardrails to Explainability to Regulation, Singapore, April 2025
• Alessandro Chillico, Domenico Vitali, Wojciech Samek, Olof Bengtsson
  Automated on-Wafer Radio-Frequency Transistor Characterization with Adaptive Probing and Features Extraction with Uncertainties,
  International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, Turin, Italy, April 2025
• Johanna Vielhaben, Dilyara Bareeva, Jim Berend, Wojciech Samek, Nils Strodthoff
  Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers,
  ICLR 2025 Workshop on Representational Alignment (Re-Align), Singapore, April 2025
• Gabriel Nobis, Arina Belova, Maximilian Springenberg, Rembert Daems, Christoph Knochenhauer, Manfred Opper, Tolga Birdal, Wojciech Samek
  Fractional Brownian Bridges for Aligned Data,
  ICLR 2025 Workshop on Learning Meaningful Representations of Life (LMRL), Singapore, April 2025
• Leander Weber, Jim Berend, Moritz Weckbecker, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
  Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation,
  ICLR 2025 Workshop: XAI4Science: From Understanding Model Behavior to Discovering New Scientific Knowledge, Singapore, April 2025
• Ekkehard Schnoor, Malik Tiomoko, Jawher Said, Sebastian Lapuschkin, Wojciech Samek
  Concept Activation Vectors from a Statistical Learning Perspective,
  DAGSTAT2025, Berlin, Germany, March 2025

2024

• Jonas Naujoks, Aleksander Krasowski, Moritz Weckbecker, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek, René P. Klausen
  PINNfluence: Influence Functions for Physics-Informed Neural Networks,
  NeurIPS'24 Workshop on Machine Learning and the Physical Sciences, Vancouver, Canada, December 2024
• Gabriel Nobis, Maximilian Springenberg, Marco Aversa, Michael Detzel, Rembert Daems, Roderick Murray-Smith, Shinichi Nakajima, Sebastian Lapuschkin, Stefano Ermon, Tolga Birdal, Manfred Opper, Christoph Knochenhauer, Luis Oala, Wojciech Samek
  Generative Fractional Diffusion Models,
  Advances in Neural Information Processing Systems 37 (NeurIPS), Vancouver, Canada, December 2024
• Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov
  CoSy: Evaluating Textual Explanations of Neurons,
  NeurIPS, Vancouver, December 2024, arXiv: https://arxiv.org/abs/2405.20331
• Dilyara Bareeva, Galip Ümit Yolcu, Anna Hedström, Niklas Schmolenski, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
  Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond,
  NeurIPS'24 Workshop on Attributing Model Behavior at Scale (ATTRIB), Vancouver, Canada, December 2024, arXiv: https://arxiv.org/abs/2410.07158
• Michael Detzel, Gabriel Nobis, Jackie Ma, Wojciech Samek
  Spatial Shortcuts in Graph Neural Controlled Differential Equations,
  NeurIPS'24 Workshop on Data-driven and Differentiable Simulations, Surrogates, and Solvers (D3S3), Vancouver, Canada, December 2024
• Maximilian Andreas Höfler, Tatsiana Mazouka, Karsten Müller, Wojciech Samek
  Boosting Federated Learning with Diffusion Models for Non-IID and Imbalanced Data,
  IEEE International Conference on Big Data, Washington DC, USA, December 2024
• Sayed M. V. Hatefi, Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
  Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers,
  ECCV'24 Workshop on Explainable Computer Vision (eXCV), Milan, Italy, September 2024
• Rohan Reddy Mekala, Frederik Pahde, Simon Baur, Sneha Chandrashekar, Madeline Diep, Markus Wenzel, Eric Wisotzky, Galip Ümit Yolcu, Sebastian Lapuschkin, Jackie Ma, Peter Eisert, Mikael Lindvall, Adam Porter, Wojciech Samek
  Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization,
  ECCV'24 Workshop on Synthetic Data for Computer Vision (SyntheticData4CV), Milano, Italy, September 2024
• Maximilian A. Höfler, Karsten Müller, Wojciech Samek
  XAI-guided Insulator Anomaly Detection for Imbalanced Datasets,
  ECCV'24 Workshop on Vision-Based Industrial Inspection (VISION), Milan, Italy, September 2024
• Brielen Madureira, Patrick Kahardipraja, David Schlangen
  When Only Time Will Tell: Interpreting How Transformers Process Local Ambiguities Through the Lens of Restart-Incrementality,
  Association for Computational Linguistics, Bangkok, Thailand, August 2024, arXiv: https://arxiv.org/abs/2402.13113
• Reduan Achtibat, Sayed M. V. Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek
  AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers,
  Proceedings of the 41st International Conference on Machine Learning (ICML), Vienna, Austria, pp. 135-168, July 2024, arXiv: https://proceedings.mlr.press/v235/achtibat24a.html
• Przemyslaw Biecek, Wojciech Samek
  Position: Explain to Question not to Justify,
  Proceedings of the 41st International Conference on Machine Learning (ICML), Vienna, Austria, pp. 3996-4006, July 2024, arXiv: https://proceedings.mlr.press/v235/biecek24a.html
• Christian Tinauer, Anna Damulina, Maximilian Sackl, Martin Soellradl, Reduan Achtibat, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Reinhold Schmidt, Stefan Ropele, Wojciech Samek, Christian Langkammer
  Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification,
  Explainable Artificial Intelligence, Second World Conference, xAI 2024, Valletta, Malta, Springer, Cham, pp. 202-216, July 2024, doi: 10.1007/978-3-031-63797-1_11, arXiv: https://arxiv.org/abs/2404.10433
• Xiaoyan Yu, Jannik Franzen, Wojciech Samek, Marina M.-C. Höhne, Dagmar Kainmüller
  Model guidance via explanations turns image classifiers into segmentation models,
  Explainable Artificial Intelligence, Second World Conference, xAI 2024,, Valletta, Malta, Springer, Cham, pp. 113-129, July 2024, doi: 10.1007/978-3-031-63797-1_7, arXiv: https://arxiv.org/abs/2407.03009
• Tobias Labarta, Elizaveta Kulicheva, Ronja Froelian, Christian Geißler, Xenia Melman, Julian von Klitzing
  Study on the Helpfulness of Explainable Artificial Intelligence,
  Second World Conference, xAI 2024, Valletta, Malta, Springer Nature Switzerland, July 2024, doi: https://doi.org/10.1007/978-3-031-63803-9_16
• Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Kirill Bykov
  Manipulating Feature Visualizations with Gradient Slingshots,
  ICML 2024, Mechanistic Interpretability Workshop / AI Safety Workshop, Vienna, Austria, July 2024, arXiv: https://arxiv.org/abs/2401.06122
• Bernhard Föllmer, Kenrick Schulze, Christian Wald, Sebastian Stober, Wojciech Samek, Marc Dewey
  Active Learning with the nnUNet and Sample Selection with Uncertainty-Aware Submodular Mutual Information Measure,
  Proceedings of the Medical Imaging with Deep Learning (MIDL), Paris, France, July 2024
• Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin
  Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, pp. 3491-3501, June 2024, doi: 10.1109/CVPRW63382.2024.00353, arXiv: https://arxiv.org/abs/2311.16681
• Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin
  Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, pp. 3532-3541, June 2024, doi: 10.1109/CVPRW63382.2024.00357, arXiv: https://arxiv.org/abs/2404.09601
• Maximilian Dreyer, Erblina Purelku, Johanna Vielhaben, Wojciech Samek, Sebastian Lapuschkin
  PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, pp. 8212-8217, June 2024, arXiv: https://arxiv.org/abs/2404.06453
• Leon Witt, Armando Teles Fortes, Kentaroh Toyoda, Wojciech Samek, Dan Li
  Blockchain and Artificial Intelligence: Synergies and Conflicts,
  Proceedings of the Workshop on Blockchain and Artificial Intelligence (BCAI), Singapore, June 2024
• Leon Witt, Kentaroh Toyoda, Wojciech Samek, Dan Li
  Democratizing Federated Learning with Blockchain and Multi-Task Peer Prediction,
  Proceedings of the Workshop on Blockchain and Artificial Intelligence (BCAI), Singapore, June 2024
• Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina Höhne
  A Fresh Look at Sanity Checks for Saliency Maps,
  Second World Conference, xAI 2024, Valletta, Malta, May 2024
• Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
  From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space,
  Proceedings of the Thirty-Eight AAAI Conference on Artificial Intelligence, Vancouver, Canada, AAAI , pp. 21046-21054, March 2024, doi: https://doi.org/10.1609/aaai.v38i19.30096

2023

• Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek
  Explainable AI for Audio via Virtual Inspection Layers,
  NeurIPS'23 Workshop on Machine Learning for Audio, New Orleans, USA, December 2023
• Gabriel Nobis, Marco Aversa, Maximilian Springenberg, Michael Detzel, Stefano Ermon, Shinichi Nakajima, Roderick Murray-Smith, Sebastian Lapuschkin, Christoph Knochenhauer, Luis Oala, Wojciech Samek
  Generative Fractional Diffusion Models,
  NeurIPS 2023 Workshop on Diffusion, New Orleans, USA, December 2023
• Karam Dawoud, Wojciech Samek, Sebastian Lapuschkin, Sebastian Bosse
  Human-Centered Evaluation of XAI Methods,
  ICDM'23 Workshop on Causal and Explainable Artificial Intelligence (CXAI), Shanghai, China, pp. 912-921, December 2023, doi: 10.1109/ICDMW60847.2023.00122
• Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala
  DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology,
  Advances in Neural Information Processing Systems 36 (NeurIPS), New Orleans, USA, pp. 78126-78141, December 2023
• Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina M.-C. Höhne
  Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test,
  NeurIPS 2023, New Orleans, Canada, October 2023, doi: https://openreview.net/forum?id=vVpefYmnsG
• Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin
  Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models,
  Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023, Vancouver, Canada, Springer, Cham, pp. 596-606, October 2023, doi: 10.1007/978-3-031-43895-0_56
• Annika Frommholz, Fabian Seipel, Sebastian Lapuschkin, Wojciech Samek, Johanna Vielhaben
  XAI-based Comparison of Audio Event Classifiers with Different Input Representations,
  20th International Conference on Content-based Multimedia Indexing (CBMI), Orleans, France, ISBN: 9798400709128, September 2023
• Daniel Becking, Paul Haase, Heiner Kirchhoffer, Karsten Müller, Wojciech Samek, Detlev Marpe
  NNCodec: An Open Source Software Implementation of the Neural Network Coding ISO/IEC Standard,
  ICML'23 Workshop on Neural Compression, Hawaii, USA, July 2023
• Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti
  Data Models for Dataset Drift Controls in Machine Learning With Optical Images,
  ICML'23 Workshop on Spurious correlations, Invariance, and Stability (SCIS), Hawaii, USA, June 2023
• Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, pp. 16143-16152, June 2023, doi: 10.1109/CVPR52729.2023.01549
• Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin
  Optimizing Explanations by Network Canonization and Hyperparameter Search,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, Canada, pp. 3818-3827, June 2023, doi: 10.1109/CVPRW59228.2023.00396
• Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
  Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, Canada, pp. 3828-3838, June 2023, doi: 10.1109/CVPRW59228.2023.00397
• Daniel Krakowczyk, Paul Prasse, David Robert Reich, Sebastian Lapuschkin, Tobias Scheffer, Lena Ann Jäger
  Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models,
  ACM, Tübingen, Germany, May 2023, doi: https://doi.org/10.1145/3588015.3588412, arXiv: https://arxiv.org/abs/2304.13536, Best Short Paper Award

2022

• Daniel Krakowczyk, David Robert Reich, Paul Prasse, Sebastian Lapuschkin, Lena Ann Jäger, Tobias Scheffer
  Selection of XAI Methods Matters: Evaluation of Feature Attribution Methods for Oculomotoric Biometric Identification,
  NeuRIPS, New Orleans, USA, November 2022, doi: https://openreview.net/pdf?id=GOLdDAP2AtI
• Gerhard Tech, Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Jonathan Pfaff, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  History Dependent Significance Coding for Incremental Neural Network Compression,
  IEEE International Conference on Image Processing (ICIP), Bordeaux, France, pp. 3541-3545, October 2022, doi: 10.1109/ICIP46576.2022.9897825
• Franz Motzkus, Leander Weber, Sebastian Lapuschkin
  Measurably Stronger Explanation Reliability Via Model Canonization,
  IEEE, Bordeaux, France, IEEE, pp. 516-520, October 2022, doi: 10.1109/ICIP46576.2022.9897282
• Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin
  Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI,
  Springer, Cham, Springer, Cham, ISBN: 978-3-031-14463-9, pp. 1-18, August 2022, doi: 10.1007/978-3-031-14463-9_1, arXiv: https://arxiv.org/abs/2205.01929
• Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek
  Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning,
  IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), New Orleans, USA, pp. 3366-3375, June 2022, doi: 10.1109/CVPRW56347.2022.00380

2021

• Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  Encoder Optimizations for the NNR Standard on Neural Network Compression,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Anchorage, AK, USA, pp. 3522-3526, September 2021, doi: 10.1109/ICIP42928.2021.9506655
• Johanna Vielhaben, Markus Wenzel, Eva Weicken, Nils Strodthoff
  Predicting the Binding of SARS-CoV-2 Peptides to the Major Histocompatibility Complex with Recurrent Neural Networks,
  ICLR 2021 Workshop: Machine Learning for Preventing and Combating Pandemics, virtual, May 2021, arXiv: https://arxiv.org/abs/2104.08237
• Jan Macdonald, Maximilian März, Luis Oala, Wojciech Samek
  Interval Neural Networks as Instability Detectors for Image Reconstructions,
  Bildverarbeitung für die Medizin - Algorithmen - System - Anwendungen, Regensburg, Germany, March 2021
• Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder
  Explanation-Guided Training for Cross-Domain Few-Shot Classification,
  25th International Conference on Pattern Recognition (ICPR), Milan, Italy, pp. 7609-7616, January 2021, doi: 10.1109/ICPR48806.2021.9412941
• Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder
  Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution,
  Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, pp. 4949-4956, January 2021, doi: 10.1109/ICPR48806.2021.9413242

2020

• Luis Oala, Jana Fehr, Luca Gilli, Pradeep Balachandran, Alixandro Werneck Leite, Saul Calderon-Ramirez, Danny Xie Li, Gabriel Nobis, Erick Alejandro Munoz Alvarado, Giovanna Jaramillo-Gutierrez, Christian Matek, Ferath Kherif, Bruno Sanguinetti, Thomas Wiegand
  ML4H Auditing: From Paper to Practice,
  Proceedings of the Machine Learning for Health NeurIPS Workshop, virtual event, December 2020
• Luis Oala, Cosmas Heiß, Jan Macdonald, Maximilian Maerz, Wojciech Samek, Gitta Kutyniok
  Detecting Failure Modes in Image Reconstructions with Interval Neural Network Uncertainty,
  Proceedings of the ICML'20 Workshop on Uncertainty & Robustness in Deep Learning, Vienna, Austria, July 2020
• Paul Haase, Heiko Schwarz, Heiner Kirchhoffer, Simon Wiedemann, Talmaj Marinc, Arturo Marban, Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  Dependent Scalar Quantization for Neural Network Compression,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, pp. 36-40, July 2020, doi: 10.1109/ICIP40778.2020.9190955
• David Neumann, Felix Sattler, Heiner Kirchhoffer, Simon Wiedemann, Karsten Müller, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek
  DeepCABAC: Plug&Play Compression of Neural Network Weights and Weight Updates,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, pp. 21-25, July 2020, doi: 10.1109/ICIP40778.2020.9190821
• Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder
  Understanding Image Captioning Models beyond Visualizing Attention,
  ICML'20 Workshop on Extending Explainable AI Beyond Deep Models and Classifiers (XXAI), Vienna, Austria, July 2020
• Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder
  Explain and Improve: Cross-Domain-Few-Shot-Learning Using Explanations,
  ICML'20 Workshop on Extending Explainable AI Beyond Deep Models and Classifiers (XXAI), Vienna, Austria, July 2020
• Christopher J. Anders, David Neumann, Talmaj Marinc, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
  XAI for Analyzing and Unlearning Spurious Correlations in ImageNet,
  ICML'20 Workshop on Extending Explainable AI Beyond Deep Models and Classifiers (XXAI), Vienna, Austria, July 2020
• Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin
  Towards best practice in explaining neural network decisions with LRP,
  Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, pp. 1-7, July 2020, doi: 10.1109/IJCNN48605.2020.9206975
• Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek
  Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training,
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, pp. 3096-3104, June 2020, doi: 10.1109/CVPRW50498.2020.00368
• Arturo Marban, Daniel Becking, Simon Wiedemann, Wojciech Samek
  Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T),
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, pp. 3105-3113, June 2020, doi: 10.1109/CVPRW50498.2020.00369
• Felix Sattler, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek
  On the Byzantine Robustness of Clustered Federated Learning,
  IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, pp. 8861-8865, May 2020, doi: 10.1109/ICASSP40776.2020.9054676
• Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima
  Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance,
  Thirty-Fourth AAAI Conference on Artificial Intelligence, New York, USA, pp. 5842-5850, February 2020, doi: 10.1609/aaai.v34i04.6042
• Grégoire Montavon, Wojciech Samek
  Explaining the decisions of deep neural networks and beyond,
  Statistics meets Machine Learning, Report No. 4/2020, Oberwolfach, Germany, Mathematisches Forschungsinstitut Oberwolfach, pp. 5-8, January 2020, doi: 10.14760/OWR-2020-4

2019

• Felix Sattler, Klaus-Robert Müller, Wojciech Samek
  Clustered Federated Learning,
  NeurIPS'19 Workshop on Federated Learning for Data Privacy and Confidentiality, Vancouver, Canada, December 2019
• Johanna Vielhaben, Hüseyin Camalan, Wojciech Samek, Markus Wenzel
  Viewport Forecasting in 360° Virtual Reality Videos with Machine Learning,
  IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), San Diego, CA, pp. 74-81, December 2019, doi: 10.1109/AIVR46125.2019.00020
• Armin W. Thomas, Klaus-Robert Müller, Wojciech Samek
  Deep Transfer Learning For Whole-Brain fMRI Analyses,
  OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, Lecture Notes in Computer Science, Shenzhen, China, Springer, Cham, pp. 59-67, October 2019, doi: 10.1007/978-3-030-32695-1_7
• Vignesh Srinivasan, Ercan E. Kuruoglu, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima
  Black-Box Decision based Adversarial Attack with Symmetric alpha-stable Distribution,
  27th European Signal Processing Conference (EUSIPCO 2019), A Coruna, Spain, pp. 1-5, September 2019, doi: 10.23919/EUSIPCO.2019.8902630
• Jan Laermann, Wojciech Samek, Nils Strodthoff
  Achieving Generalizable Robustness of Deep Neural Networks by Stability Training,
  Pattern Recognition - 41st DAGM German Conference, DAGM GCPR 2019, Lecture Notes in Computer Science, Dortmund, Germany, Springer International Publishing, pp. 360-373, September 2019, doi: 10.1007/978-3-030-33676-9_25
• Talmaj Marinc, Vignesh Srinivasan, Serhan Gül, Cornelius Hellge, Wojciech Samek
  Multi-Kernel Prediction Networks for Denoising of Burst Images,
  IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, pp. 2404-2408, September 2019, doi: 10.1109/ICIP.2019.8803335
• Leila Arras, Ahmed Osman, Klaus-Robert Müller, Wojciech Samek
  Evaluating Recurrent Neural Network Explanations,
  ACL'19 Workshop on BlackboxNLP, Florence, Italy, pp. 113-126, August 2019, doi: 10.18653/v1/W19-4813
• Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
  Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication,
  IEEE International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, pp. 1-8, July 2019, doi: 10.1109/IJCNN.2019.8852172
• Simon Wiedemann, Arturo Marban, Klaus-Robert Müller, Wojciech Samek
  Entropy-Constrained Training of Deep Neural Networks,
  IEEE International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, pp. 1-8, July 2019, doi: 10.1109/IJCNN.2019.8852119
• Patrick Wagner, Jakob P. Morath, Arturo Zychlinsky, Wojciech Samek
  Rotation Invariant Clustering of 3D Cell Nuclei Shapes,
  41th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, pp. 6022-6027, July 2019, doi: 10.1109/EMBC.2019.8856734
• Vignesh Srinivasan, Arturo Marban, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima
  Robustifying Models Against Adversarial Attacks by Langevin Dynamics,
  36th International Conference on Machine Learning ICML'19, Workshop on Uncertainty & Robustness in Deep Learning , Long Beach, CA, USA, June 2019
• Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, Heiko Schwarz, Detlev Marpe, Thomas Wiegand, Ahmed Osman, Wojciech Samek
  DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression,
  International Conference on Machine Learning, Joint ICML’19 Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations (ODML-CDNNR), Long Beach, CA, USA, June 2019, Best Paper Award

2018

• Nils Strodthoff, Baris Göktepe, Thomas Schierl, Wojciech Samek, Cornelius Hellge
  Machine Learning for early HARQ Feedback Prediction in 5G,
  IEEE Global Communications Conference (Globecom Workshops), Abu Dhabi, UAE, pp. 1-6, December 2018, doi: 10.1109/GLOCOMW.2018.8644343
• Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
  Compact and Computationally Efficient Representation of Deep Neural Networks,
  NIPS Workshop on Compact Deep Neural Network Representation with Industrial Applications (CDNNRIA), Montreal, Canada, pp. 1-6, December 2018
• Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
  How to iNNvestigate neural network’s predictions!,
  NIPS Workshop on Machine Learning Open Source Software (MLOSS), Montreal, Canada, pp. 1-6, December 2018
• Sebastian Bosse, Sören Becker, Zacharias V. Fisches, Wojciech Samek, Thomas Wiegand
  Neural Network-based Estimation of Distortion Sensitivity for Image Quality Prediction,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Athens, Kefalonia, Greece, pp. 629-633, October 2018, doi: 10.1109/ICIP.2018.8451261
• Arturo Marban, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals
  Estimation of Interaction Forces in Robotic Surgery using a Semi-Supervised Deep Neural Network Model,
  IEEE/RSJ International Conference on Intelligent Robots (IROS), Madrid, Spain, pp. 761-768, October 2018, doi: 10.1109/IROS.2018.8593701
• Jonathan Pfaff, Philipp Helle, Dominique Maniry, Stephan Kaltenstadler, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  Neural Network based Intra Prediction for Video Coding,
  SPIE 10752, Applications of Digital Image Processing XLI, San Diego, USA, September 2018, doi: 10.1117/12.2321273
• Sebastian Bosse, Milena Bagdasarian, Wojciech Samek, Gabriel Curio, Thomas Wiegand
  On the Stimulation Frequency in SSVEP-based Image Quality Assessment,
  Proceedings of the 10th International Conference on Quality of Multimedia Experience (QoMEX), Sardinia, Italy, pp. 1-6, May 2018, doi: 10.1109/QoMEX.2018.8463381
• Christopher Ehmann, Wojciech Samek
  Transferring Information between Neural Networks,
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, pp. 2361-2365, April 2018, doi: 10.1109/ICASSP.2018.8461511

2017

• Sebastian Lapuschkin, Alexander Binder, Klaus-Robert Müller, Wojciech Samek
  Understanding and Comparing Deep Neural Networks for Age and Gender Classification,
  Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCVW), Venice, Italy, pp. 1629-1638, October 2017, doi: 10.1109/iccvw.2017.191
• Arturo Marban, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals
  Estimating Position & Velocity in 3D Space from Monocular Video Sequences using a Deep Neural Network,
  Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCVW), Venice, Italy, pp. 1460-1469, October 2017, doi: 10.1109/iccvw.2017.173
• Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  Explaining Recurrent Neural Network Predictions in Sentiment Analysis,
  Proceedings of the EMNLP'17, Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA), Denmark, Copenhagen, Denmark, pp. 159-168, September 2017, doi: 10.18653/v1/W17-5221
• Sebastian Bosse, Mischa Siekmann, Wojciech Samek, Thomas Wiegand
  A Perceptually Relevant Shearlet-Based Adaptation of the PSNR,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Beijing, China, pp. 315-319, September 2017, doi: 10.1109/icip.2017.8296294
• Forooz Shahbazi Avarvand, Sebastian Bosse, Guido Nolte, Thomas Wiegand, Wojciech Samek
  Measuring the Quality of 3D Visualizations using EEG: A Time-Frequency Approach,
  Proceedings of 7th Graz Brain-Computer Interface Conference, Graz, Austria, pp. 441-446, September 2017, doi: 10.3217/978-3-85125-533-1-81
• Clemens Peter Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert
  Detection of Face Morphing Attacks by Deep Learning,
  Proceedings of the 16th International Workshop on Digital Forensics and Watermarking (IWDW2017), Magdeburg, Germany, pp. 107-120, August 2017, doi: 10.1007/978-3-319-64185-0_9
• Forooz Shahbazi Avarvand, Sebastian Bosse, Guido Nolte, Thomas Wiegand, Wojciech Samek
  Quality Assessment of 3D Visualizations with Vertical Disparity: An ERP Approach,
  Proceedings of 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jeju Island, South Korea, pp. 4391-4394, July 2017, doi: 10.1109/embc.2017.8037829
• Vignesh Srinivasan, Sebastian Lapuschkin, Cornelius Hellge, Klaus-Robert Müller, Wojciech Samek
  Interpretable human action recognition in compressed domain,
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), LA, New Orleans, Louisiana, USA, pp. 1692-1696, March 2017, doi: 10.1109/icassp.2017.7952445

2016

• Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller
  Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation,
  Proceedings of the Interpretable ML for Complex Systems Workshop at the Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016
• Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek
  Neural Network-Based Full-Reference Image Quality Assessment,
  Proceedings of the Picture Coding Symposium (PCS), Nürnberg, Germany, pp. 1-5, December 2016, doi: 10.1109/pcs.2016.7906376
• Vignesh Srinivasan, Serhan Gül, Sebastian Bosse, Jan Timo Meyer, Thomas Schierl, Cornelius Hellge, Wojciech Samek
  On the robustness of action recognition methods in compressed and pixel domain,
  Proceedings of the European Workshop on Visual Information Processing (EUVIP), Marseille, France, pp. 1-6, October 2016, doi: 10.1109/euvip.2016.7764584
• Sebastian Bosse, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek
  Brain-Computer Interfacing for Multimedia Quality Assessment,
  Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, pp. 002834-002839, October 2016, doi: 10.1109/smc.2016.7844669
• Stephanie Brandl, Klaus-Robert Müller, Wojciech Samek
  Alternative CSP approaches for multimodal distributed BCI data,
  Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, pp. 003742-003747, October 2016, doi: 10.1109/smc.2016.7844816
• Serhan Gül, Jan Timo Meyer, Thomas Schierl, Cornelius Hellge, Wojciech Samek
  Hybrid Video Object Tracking in H.265/HEVC Video Streams,
  Proceedings of the International Workshop on Multimedia Signal Processing (MMSP), Montreal, Canada, pp. 1-5, September 2016, doi: 10.1109/mmsp.2016.7813363
• Sebastian Bosse, Qiaobo Chen, Mischa Siekmann, Wojciech Samek, Thomas Wiegand
  Shearlet-based Reduced Reference Image Quality Assessment,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Phoenix, Arizona, USA, pp. 2052-2056, September 2016, doi: 10.1109/icip.2016.7532719
• Sebastian Bosse, Dominique Maniry, Thomas Wiegand, Wojciech Samek
  A Deep Neural Network for Image Quality Assessment,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Phoenix, Arizona, USA, pp. 3773-3777, September 2016, doi: 10.1109/icip.2016.7533065
• Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek
  Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth,
  Proceedings of the IEEE International Conference on Image Processing (ICIP), Phoenix, Arizona, USA, pp. 2271-2275, September 2016, doi: 10.1109/icip.2016.7532763
• Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  Explaining Predictions of Non-Linear Classifiers in NLP,
  Proceedings of the Workshop on Representation Learning for NLP at Association for Computational Linguistics Conference (ACL), Berlin, Germany, pp. 1-7, August 2016, doi: 10.18653/v1/w16-1601
• Sebastian Bosse, Mischa Siekmann, Jennifer Rasch, Thomas Wiegand, Wojciech Samek
  Quality Assessment of Image Patches Distorted by Image Compression Using Crowdsourcing,
  Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), Seattle, Washington, USA, pp. 1-6, July 2016, doi: 10.1109/icme.2016.7552958
• Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  Analyzing Classifiers: Fisher Vectors and Deep Neural Networks,
  Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, Nevada, USA, pp. 2912-2920, June 2016, doi: 10.1109/cvpr.2016.318
• Alexander Binder, Wojciech Samek, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller
  Analyzing and Validating Neural Networks Predictions,
  Proceedings of the Workshop on Visualization for Deep Learning at 33rd International Conference on Machine Learning (ICML), New York City, USA, June 2016, best paper award
• Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek
  Full-Reference Image Quality Assessment Using Neural Networks,
  Proceedings of the 8th International Conference on Quality of Multimedia Experience (QoMEX), Lisbon, Portugal, June 2016
• Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller
  Deep Taylor Decomposition of Neural Networks,
  Proceedings of the Workshop on Visualization for Deep Learning at 33rd International Conference on Machine Learning (ICML), New York City, USA, June 2016

2015

• Carmen Vidaurre, Claudia Sannelli, Wojciech Samek, Sven Dähne, Klaus-Robert Müller
  Machine Learning Methods of the Berlin Brain-Computer Interface,
  Proceedings of the 9th IFAC Symposium on Biological and Medical Systems, Berlin, Germany, pp. 447-452, September 2015, doi: 10.1016/j.ifacol.2015.10.181
• Detlef Ruschin
  Maintaining patients' social contacts through displaying nonverbal awareness information on mobile devices,
  Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy, pp. 7744-7747, August 2015, doi: 10.1109/embc.2015.7320187
• Wojciech Samek, Klaus-Robert Müller
  Tackling noise, artifacts and nonstationarity in BCI with robust divergences,
  Proceedings of the European Signal Processing Conference (EUSIPCO), Nice, France, pp. 2791-2795, August 2015, doi: 10.1109/eusipco.2015.7362883
• Laura Frølich, Irene Winkler, Klaus-Robert Müller, Wojciech Samek
  Investigating effects of different artefact types on Motor Imagery BCI,
  Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy, pp. 1942-1945, August 2015, doi: 10.1109/embc.2015.7318764
• Stephanie Brandl, Johannes Höhne, Klaus-Robert Müller, Wojciech Samek
  Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment,
  Proceedings of the International IEEE/EMBS Neural Engineering Conference (NER), Montpellier, France, pp. 224-227, April 2015, doi: 10.1109/ner.2015.7146600
• Stephanie Brandl, Klaus-Robert Müller, Wojciech Samek
  Robust Common Spatial Patterns based on Bhattacharyya Distance and Gamma Divergence,
  Proceedings of the IEEE International Winter Workshop on Brain-Computer Interface (BCI), Jeongsun-Kun, South Korea, pp. 1-4, January 2015, doi: 10.1109/iww-bci.2015.7073030

2014

• Dirk Wilhelm, Silvano Reiser, Nils Kohn, Michael Witte, Ulrich Leiner, Lothar Mühlbach, Detlef Ruschin, Wolfgang Reiner, Hubertus Feussner
  Comprehensive evaluation of latest 2D/3D monitors and comparison to a custom-built 3D mirror-based display in laparoscopic surgery,
  Proceedings of SPIE 9011, Stereoscopic Displays and Applications XXV, San Francisco, California, USA, March 2014, doi: 10.1117/12.2040040

2025

• Daniel Becking, Karsten Müller
  [NNC] EE1.2 on Low Overhead Gradients and Activations Coding for Split Learning,
  ISO/IEC JTC1/SC29/WG4/m71127, January 2025

2024

• Daniel Becking, Karsten Müller, Paul Haase, Gerhard Tech
  [NNC] Updates to Reference Software for Conformance Bitstreams and Draft Text of FDIS ISO/IEC 15938-18ed2,
  ISO/IEC JTC1/SC29/WG04/m68827, July 2024
• Daniel Becking, Karsten Müller, Paul Haase, Gerhard Tech, Heiner Kirchhoffer, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] Initial Insights into Coding Large Language Models (LLMs) with NNCodec,
  ISO/IEC JTC1/SC29/WG04/m66483, January 2024

2023

• David Neumann, Andreas Lutz, Karsten Müller, Wojciech Samek
  [NNC] Neural Network Coding in Recommender System Use Case,
  ISO/IEC JTC1/SC29/WG04/m59331, April 2023
• Heiner Kirchhoffer, Paul Haase, Daniel Becking, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] Bug report on CABAC entry point signaling in ISO/IEC FDIS 15938-17 edition 1,
  ISO/IEC JTC1/SC29/WG04/m63092, April 2023
• Paul Haase, Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] NNCodec: An open NNC encoder/decoder implementation,
  ISO/IEC JTC1/SC29/WG04/m61972, January 2023

2022

• Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Daniel Becking, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] Clarification on colocated context derivation for temporal context modeling,
  ISO/IEC JTC1/SC29/WG04/m61115, October 2022
• David Neumann, Karsten Müller, Wojciech Samek
  [NNC] Neural Network Coding in Recommender System Use Case,
  ISO/IEC JTC1/SC29/WG04/m59331, April 2022
• Karsten Müller, Heiner Kirchhoffer, Paul Haase, Daniel Becking, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] Communication Patterns in Federated Learning utilizing PUT,
  ISO/IEC JTC1/SC29/WG04/m59504, April 2022
• Paul Haase, Heiner Kirchhoffer, Karsten Müller, Daniel Becking, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] Tensor dimension reordering by tensor dimension shift,
  ISO/IEC JTC1/SC29/WG04/m59534, April 2022
• Daniel Becking, Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] BatchNorm Folding Update for ICNN,
  ISO/IEC JTC1/SC29/WG04/m59535, April 2022
• Gerhard Tech, Paul Haase, Heiner Kirchhoffer, Daniel Becking, Karsten Müller, Heiko Schwarz, Jonathan Pfaff, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  [NNC] CE3-related: History Dependent Significance Probability Derivation,
  ISO/IEC JTC1/SC29/WG04/m58810, January 2022
• Paul Haase, Heiner Kirchhoffer, Karsten Müller, Daniel Becking, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] CE3-related: CABAC adaptation for binary/ternary codebooks,
  ISO/IEC JTC1/SC29/WG04/m58848, January 2022
• Daniel Becking, Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] General Local Scaling Adaptation with Warm Restarts for Incremental Neural Network Compression,
  ISO/IEC JTC1/SC29/WG04/m58821, January 2022
• Daniel Becking, Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNC] V1-V2-Harmonized and Revised Test Model Software of ICNN,
  ISO/IEC JTC1/SC29/WG04/m58825, January 2022

2021

• Karsten Müller, Paul Haase, Heiner Kirchhoffer, Daniel Becking, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR] Naming Proposal "Neural Network Coding – NNC" for ISO/IEC 15938-17,
  ISO/IEC JTC1/SC29/WG04/m58067, October 2021
• Paul Haase, Heiner Kirchhoffer, Karsten Müller, Daniel Becking, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR] Conformance Bitstreams for ISO/IEC 15938-18,
  ISO/IEC JTC1/SC29/WG04/m58093, October 2021
• Paul Haase, Heiner Kirchhoffer, Karsten Müller, Daniel Becking, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR] Error report on ISO/IEC FDIS 15938-17 and proposed solutions,
  ISO/IEC JTC1/SC29/WG04/m58247, October 2021
• Daniel Becking, Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR] CE1: Report on HHI Results for Incremental Neural Network Compression,
  ISO/IEC JTC1/SC29/WG04/m58068, October 2021
• Paul Haase, Heiner Kirchhoffer, Daniel Becking, Gerhard Tech, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR] CE1-CE3: Report on HHI Results for Incremental Neural Network Compression,
  ISO/IEC JTC1/SC29/WG4/m57416, July 2021
• Heiner Kirchhoffer, Karsten Müller, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] Batch norm unfolding clarification for DIS of ISO/IEC 15938-17,
  ISO/IEC JTC1/SC29/WG4 MPEG2021/m56748, April 2021
• Heiner Kirchhoffer, Daniel Becking, Karsten Müller, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] Generic topology storage format for DIS of ISO/IEC 15938-17,
  ISO/IEC JTC1/SC29/WG4 MPEG2021/m56813, April 2021
• Daniel Becking, Paul Haase, Gerhard Tech, Heiner Kirchhoffer, Karsten Müller, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  [NNR] Response to the Call for Proposals on incremental compression of neural networks for multimedia content description and analysis,
  ISO/IEC JTC1/SC29/WG4 MPEG2021/m56621, April 2021

2020

• Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Wojciech Samek, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] CE4 method 19: Results on QP optimizations,
  ISO/IEC JTC1/SC29/WG4 MPEG2020/m55073, online meeting, October 2020
• Heiner Kirchhoffer, Karsten Müller, Wojciech Samek, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] Committee draft cleanups, improvements, and bug fixes,
  ISO/IEC JTC1/SC29/WG4 MPEG2020/m55068, online meeting, October 2020
• Heiner Kirchhoffer, Paul Haase, Karsten Müller, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] HLS for parallel CABAC decoding including parameter optimizations,
  online meeting, ISO/IEC JTC1/SC29/WG4 MPEG2020/m55066, October 2020
• Heiner Kirchhoffer, Karsten Müller, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] Harmonization of codebook quantization and NNR_PT_BLOCK compressed data payload type,
  online meeting, ISO/IEC JTC1/SC29/WG4 MPEG2020/m55575, October 2020
• Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Wojciech Samek, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  [NNR] HLS for additional framework support,
  ISO/IEC JTC1/SC29/WG4 MPEG2020/m55067, online meeting, October 2020
• Heiner Kirchhoffer, Paul Haase, Simon Wiedemann, Talmaj Marinc, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR] CE4: Results on parameter optimization for DeepCABAC (method 18) and local scaling adaptation (method 19),
  online meeting, ISO/IEC JTC1/SC29/WG11 MPEG2020/m54395, July 2020
• Paul Haase, Heiner Kirchhoffer, Karsten Müller, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR]: HLS adaptation for integer codebook representation,
  online meeting, ISO/IEC JTC1/SC29/WG11 MPEG2020/m54397, July 2020
• Heiner Kirchhoffer, Karsten Müller, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  [NNR]: Low-rank decomposition syntax for NNR compressed payload type NNR_PT_BLOCK_LS on top of m54395,
  online meeting, ISO/IEC JTC1/SC29/WG11 MPEG2020/m54806, July 2020
• Heiner Kirchhoffer, Paul Haase, Simon Wiedemann, Talmaj Marinc, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  CE4: Results on parameter optimization for DeepCABAC (method 18) and local scaling adaptation (method 19),
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m54395, Online Meeting, June 2020
• Karsten Müller, Heiner Kirchhoffer, Talmaj Marinc, Simon Wiedemann, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  Additional HLS and decoding process specification for Neural Network Compression (ISO/IEC 15938-17),
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m53518, Alpbach, Austria, April 2020
• Simon Wiedemann, Paul Haase, Heiner Kirchhoffer, Talmaj Marinc, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  CE2-CE3-related: Local parameter scaling,
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m53517, Alpbach, Austria, April 2020
• Simon Wiedemann, Paul Haase, Heiner Kirchhoffer, Talmaj Marinc, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  Results on importance-weighted quantization,
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m53516, Alpbach, Austria, April 2020
• Paul Haase, Heiner Kirchhoffer, Simon Wiedemann, Talmaj Marinc, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  CE3-related: Parameter-Optimization for DeepCABAC,
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m53515, Alpbach, Austria, April 2020
• Paul Haase, Heiner Kirchhoffer, Simon Wiedemann, Talmaj Marinc, Karsten Müller, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
  CE2-CE3: Results on dependent scalar quantization,
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m53514, Alpbach, Austria, April 2020
• Paul Haase, Heiko Schwarz, Heiner Kirchhoffer, Simon Wiedemann, Stefan Matlage, Talmaj Marinc, Arturo Marban, Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  CE2-related: Dependent scalar quantization for neural network parameter approximation,
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m52358, Brussels, Belgium, January 2020
• Karsten Müller, Robert Skupin, Yago Sanchez de la Fuente, Simon Wiedemann, Heiner Kirchhoffer, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  Basic High-Level Syntax for Neural Network Compression (ISO/IEC 15938-17, i.e. MPEG-7 part 17),
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m52352, Brussels, Belgium, January 2020
• Felix Sattler, David Neumann, Simon Wiedemann, Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand
  Test Data, Evaluation Framework and Results for NNU / Federated Learning Use Cases,
  ISO/IEC JTC1/SC29/WG11 MPEG2020/m52375, Brussels, Belgium, January 2020

2019

• Simon Wiedemann, Heiner Kirchhoffer, Wojciech Samek, Karsten Müller, Detlev Marpe, Heiko Schwarz, Thomas Wiegand
  Proposal of python interfaces for an NNR test model,
  ISO/IEC JTC1/SC29/WG11 MPEG2019/M49867, Gothenburg, Sweden, July 2019
• Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, David Neumann, Heiko Schwarz, Detlev Marpe, Wojciech Samek, Thomas Wiegand
  Report of CEs results,
  ISO/IEC JTC1/SC29/WG11 MPEG2019/m48662, Gothenburg, Sweden, July 2019
• Wojciech Samek, Vignesh Srinivasan, Luis Oala, Thomas Wiegand
  Robustness - Safety and reliability in AI4H,
  FG-AI4H-E-025, Geneva, Switzerland, May 2019
• Nils Strodthoff, Arun Shroff, Wojciech Samek
  Aspects of Evaluation Procedures for Machine Learning Algorithms,
  FG-AI4H-D-039, Shanghai, China, April 2019
• Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, David Neumann, Ahmed Osman, Heiko Schwarz, Detlev Marpe, Wojciech Samek, Thomas Wiegand
  Response to the Call for Proposals on Neural Network Compression: End-to-end processing pipeline for highly compressible neural networks,
  ISO/IEC JTC1/SC29/WG11 MPEG2019/M47698, Geneva, Switzerland, March 2019
• Wojciech Samek
  Proposal: Data selection method for evaluation of ML algorithms,
  FG-AI4H-C-027, Lausanne, Switzerland, January 2019

2018

• Wojciech Samek, Vishnu Ram
  WG2 deliverable for MPP use case,
  ITU-T FG-ML5G-I-086-R3, Tokyo, Japan, November 2018
• Wojciech Samek, Vishnu Ram
  Applying characteristics of ML techniques to optimize architectures,
  ITU-T FG-ML5G-I-112, Tokyo, Japan, November 2018
• Wojciech Samek
  Draft: Selection of representative training data for evaluation of ML algorithms,
  FG-AI4H-B-026, New York, USA, November 2018
• Wojciech Samek, Simon Wiedemann
  Efficient representations of neural networks,
  ITU-T FG-ML5G-I-102, Tokyo, Japan, November 2018
• Wojciech Samek
  Discussion of WG2 deliverable for MPP use case,
  ITU-T FG-ML5G-I-075, San Jose, USA, August 2018
• Wojciech Samek, Sebastian Troia, Francesc Wilhelmi
  Overview and Requirement Analysis of ML Methods in Communications,
  ITU-T FG-ML5G-I-032, Xi’an, China, April 2018

2017

• Wojciech Samek, Simon Wiedemann, Slawomir Stanczak, Thomas Wiegand
  Data Formats and Specifications for Efficient Machine Learning in Communications,
  ITU-T FG-ML5G-I-013, Geneva, Switzerland, January 2017

2016

• G. Weber, O. Böpple, M. Weber, Paul Chojecki, Detlef Ruschin, K. Köppe, S. Glende, et al.
  Berührungslose Gestensteuerung zur Mensch-System-Interaktion (Contactless gesture control for human-system interaction),
  DIN SPEC 91333, Berlin, Germany, August 2016

2025

• Wojciech Samek
  SemanticLens: Explaining Data, Model, Predictions and Their Interactions,
  Leopoldina Meeting "“Molekulare Einzelzellanalysen und ihre Verknüpfung mit zellulären Bewegungsmustern mittel KI", Halle, Germany, March 2025, Talk
• Wojciech Samek
  Component-level Explanation and Validation of AI Models,
  Explainable and Interpretable AI: Methods, Challenges, and Applications, Tunis, Tunesia, February 2025, Talk
• Wojciech Samek
  Panel Discussion: "Is Explainable AI our Solution to Mitigate Bias ?",
  AI House, Davos, Switzerland, January 2025, Talk

2024

• Wojciech Samek
  Explainable AI for LLMs,
  ML in PL Conference, Warsaw, Poland, November 2024, Talk
• Sebastian Lapuschkin
  XAI as a Tool Beyond Model Understanding – From Heatmaps to Concepts and XAI Automation,
  Max Planck Institute for Human CBS, CBS CoCoNUT, Leipzig, November 2024, Invited Talk
• Wojciech Samek
  Understanding & Validating LLMs with Explanations,
  AI Forum 2024, Berlin, Germany, November 2024, Talk
• Wojciech Samek
  Explainable AI,
  Konferencja Wladz Uczelnianych Matematyki i Informatyki, Krakow, Poland, November 2024, Talk
• Maximilian Dreyer
  Understanding and Monitoring Model Behavior With Concept-based Explanations,
  KAIST XAI Research Center, KAIST XAI Tutorial Series 2024, virtuell, November 2024, Invited Talk
• Reduan Achtibat
  Scaling Concept-based Explanations for Large Language Models,
  KAIST XAI Research Center , KAIST XAI Tutorial Series 2024, virtuell, November 2024, Invited Talk
• Wojciech Samek
  Wyjaśnialna sztuczna inteligencja: od metod do nowych spostrzeżeń,
  Inauguration Lecture at Warsaw University of Technology,, Warsaw, Poland, October 2024, Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  Dagstuhl Seminar 24372 "Explainable AI for Sequential Decision Making", Schloss Dagstuhl, Germany, September 2024, Talk
• Wojciech Samek
  From Feature Attributions to Next-Generation Explainable AI,
  11th International School on Deep Learning (DeepLearn), Porto, Portugal, July 2024, Talk
• Wojciech Samek
  Towards Next-Generation Explainable AI,
  DEI Open Day at University of Porto, Porto, Portugal, July 2024, Talk
• Wojciech Samek
  Explainable AI for LLMs,
  Nokia Bell Labs "Responsible AI Seminar Series", virtual talk, July 2024, Talk
• Wojciech Samek
  Explainable AI for LLMs,
  24th International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland, June 2024, Talk
• Wojciech Samek
  Explainable AI in the era of Large Language Models,
  AI for Good Global Summit, Geneva, Switzerland, May 2024, Talk
• Sebastian Lapuschkin
  Artificial Intelligence We Can Trust – From Explainable to Actionable and Regenerative AI,
  Melanoma Patient Network Europe, MPNE Consensus 2024 Workshop, Forum Digitale Technologien, Berlin, Germany, February 2024, Invited Talk
• Maximilian Dreyer
  Reveal to Revise: How to Uncover and Correct Biases of Deep Models in Medical Applications,
  Rubin Lab, Stanford University, Stanford MedAI Group Exchange Sessions, virtuell, February 2024, Invited Talk
• Sebastian Lapuschkin
  From Concepts to Prototypes / Towards Minimal Effort Post-Hoc Interpretability,
  University of Bergen, Norway, Machine Teaching 4 XAI Workshop, Valencian Research Institute for AI (VRAIN), Valen, January 2024, Invited Talk
• Wojciech Samek
  XAI-Based Model Debugging,
  Guest Lecture at Warsaw University of Technology, Warsaw, Poland, January 2024, Talk
• Wojciech Samek
  Explainable AI 2.0: From Heatmaps to Human-Understandable and Actionable Explanations,
  Machine Teaching for Human (MT4H) Workshop, Valencia, Spain, January 2024, Talk
• Wojciech Samek
  Human-Centered Explainable AI,
  DFG Graduate School BIOQIC Seminars, Berlin, Germany, January 2024, Talk

2023

• Sebastian Lapuschkin
  Explainable AI,
  Universitat de Girona, Machine Learning (Seminar), Girona, Spain, December 2023, Invited Talk
• Sebastian Lapuschkin
  Explainable AI,
  Universitat de Girona, Machine Learning Seminar, Girona, Catalonia, Spain, December 2023, Invited Talk
• Wojciech Samek
  New Opportunities and New Challenges Resulting from the AI Revolution,
  Invited Talk at Warsaw University, Warsaw, Poland, November 2023, Talk
• Wojciech Samek
  From local explanations to global understanding,
  Guest Lecture, Warsaw University of Technology, Warsaw, Poland, November 2023, Talk
• Wojciech Samek
  Human-Centered Explainable AI,
  Poznan University of Technology, Poznan, Poland, November 2023, Talk
• Wojciech Samek
  Explainability 2.0 in the era of Generative AI,
  AI Forum 2023, Berlin, Germany, November 2023, Talk
• Frederik Pahde
  Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models,
  Fairness of AI in Medical Imaging Workshop, Virtual, November 2023, arXiv: https://arxiv.org/pdf/2303.12641.pdf, Invited Talk
• Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin
  Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models,
  Fairness of AI in Medical Imaging, virtuell, November 2023, Talk
• Reduan Achtibat
  Towards eXplainable AI 2.0 with Concept-based Explanations,
  VDI/VDE-Gesellschaft Mess- und Automatisierungstec, Fachausschuss des VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik, virtuell, November 2023, Invited Talk
• Sebastian Lapuschkin
  Explaining AI with Concept Relevance Propagation,
  4th Japanese-American-German Frontiers of Science (JAGFOS) Symposium, Dresden, October 2023, Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  SPAA & Dependability@Siemens 2023, virtual talk, October 2023, Talk
• Wojciech Samek
  Explainable and Robust Machine Learning,
  4th Japanese-American-German Frontiers of Science (JAGFOS) Symposium, Dresden, Germany, September 2023, Talk
• Wojciech Samek
  The New ISO/IEC Standard for Neural Network Coding,
  ECML PKDD'23 Workshop on "Simplification, Compression, Efficiency and Frugality for Artificial intelligence", Torino, Italy, September 2023, Talk
• Wojciech Samek
  Accessing the Hidden Space of Models with Explainable AI,
  The Human Centric AI Seminars Series, virtual talk, August 2023, Talk
• Wojciech Samek
  From Black-Box Models to Human-Understandable Explainable AI,
  Bayreuth Summer School of Philosophy and Computer Science, Bayreuth, Germany, July 2023, Talk
• Sebastian Lapuschkin
  Model-Assisted Data Analysis via XAI,
  Berlin Institute of Health, 19th Machine Learning in Healthcare Meetup Berlin, Berlin, July 2023, Invited Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  IEEE CVPR'23 Workshop "Safe Artificial Intelligence for All Domains", Vancouver, Canada, June 2023, Talk
• Sebastian Lapuschkin
  Accessing the Hidden Space with Explainable Artificial Intelligence,
  Universität Bremen / Leibniz-Institut für Präventi, Informatik-Kolloquium Bremen, Bremen, June 2023, Invited Talk
• Sebastian Lapuschkin
  Explainable AI and Beyond with Concept Relevance Propagation,
  EnBW, Data Professional Days / Data4Business Days, Köln, May 2023, Invited Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  Polish Conference on Artificial Intelligence, Lodz, Poland, April 2023, Talk
• Wojciech Samek
  AI Liability, Machine Learning Research and Explainable AI,
  AI liability in the EU and the US: stifling or securing innovation, Berlin, Germany, April 2023, Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  WhiteBox Milestone Conference, Darmstadt, March 2023, Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  Workshop on "Explainability in Machine Learning", Tübingen, Germany, March 2023, Talk
• Wojciech Samek
  A gentle introduction to explainable AI,
  Spring School "Ethos+Tekhnè : A new generation of AI researchers", Pisa, Italy, March 2023, Talk
• Wojciech Samek
  Machine Learning with Little Data,
  4th Meeting of Digital Pathology, San Servolo, Italy, March 2023, Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  Workshop "Explainable AI for the Sciences: Towards Novel Insights", IPAM, January 2023, Talk
• Sebastian Lapuschkin
  Human-Understandable Explanations through Concept Relevance Propagation,
  University of Bergen, Machine Teaching for Humans Workshop, Madeira, January 2023, Invited Talk

2022

• Wojciech Samek
  Next-Generation Explainable AI,
  Max Planck School of Cognition Academy, Berlin, Germany, December 2022, Talk
• Wojciech Samek
  Methods for Explaining Deep Neural Networks and Evaluating Explanations,
  2022 Intelligent Sensing Winter School, virtual meeting, December 2022, Talk
• Wojciech Samek
  Explainable Machine Learning for the Sciences,
  Symposium of the German National Academy of Sciences - Leopoldina, Halle, Germany, November 2022, Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  3rd International Workshop on Auditing AI-Systems, Berlin, November 2022, Talk
• Wojciech Samek
  Towards Human-Understandable XAI,
  Seminar Uni Augsburg, online event, October 2022, Talk
• Wojciech Samek
  Introduction to Explainable AI,
  7th Summer School on Data Science (SSDS-2022), virtual event, October 2022, Talk
• Wojciech Samek
  Human-Machine Interactions Through Explanations,
  3rd ERCIM-JST Workshop, INRIA Rocquencourt, France, October 2022, Talk
• Wojciech Samek
  Global-Local XAI with Concept Relevance Propagation,
  2022 Workshop on Self-Supervised Learning for Signal Decoding, Aalborg, Denmark, October 2022, Talk
• Sebastian Lapuschkin
  Towards Human-understandable Explanations with XAI 2.0,
  International Telecommunications Union, AI 4 Good, Virtual/Remote, October 2022, Talk
• Sebastian Lapuschkin
  Beyond Heatmaps – Explaining with Concepts,
  BIFOLD, BIFOLD Graduate School Welcome Days, Berlin, October 2022, Invited Talk
• Wojciech Samek
  Concept-Level Explainable AI,
  Explainable AI for Wireless Communications, online event, September 2022, Talk
• Sebastian Lapuschkin
  Recent Advances in Explainable AI,
  Universität Potsdam, BB-KI-Chips Summer School Potsdam, Potsdam, September 2022, Invited Talk
• Sebastian Lapuschkin
  Towards Actionable XAI,
  Artificial Intelligence Doctoral Academy, Artificial Intelligence Doctoral Academy, Virtual/Remote, September 2022, Invited Talk
• Wojciech Samek
  Explainable AI: Concepts, Methods and Applications,
  6th International Gran Canaria School on Deep Learning, Gran Canaria, Spain, July 2022, Talk
• Wojciech Samek
  Explainable AI: Basics and Recent Developments,
  24th International Conference on Human-Computer Interactiong, virtual event, June 2022, Talk
• Wojciech Samek
  From Attribution Maps to Concept-Level Explainable AI,
  Pioneer Centre for AI Talk, Copenhagen, Denmark, June 2022, Talk
• Sebastian Lapuschkin
  Zukünftige Trends in der KI und Einsatzmöglichkeiten im Bauwesen,
  BIMKIT, BIMKIT Jahrestagung 2022, Virtuell/Remote, June 2022, Invited Talk
• Wojciech Samek
  Towards Communication-Efficient and Personalized Federated Learning,
  2021 IEEE SPS Cycle 2 School on Networked Federated Learning: Theory, Algorithms and Applications, virtual event, April 2022, Talk
• Wojciech Samek
  Explainable AI: Concepts, Methods and Recent Developments,
  Seminar on Bio-Inspired Artificial Neural Networks, virtual event, January 2022, Talk

2021

• Sebastian Lapuschkin
  Explainable AI,
  Universitat de Girona, Machine Learning (Seminar), Girona, Spain, December 2021, Invited Talk
• Wojciech Samek
  Wireless Federated Learning,
  IEEE SPAWC, Lucca, Italy, September 2021, Tutorial, Talk
• Sebastian Lapuschkin
  XAI Beyond Explaining: Using Explainability for Improving Deep Machine Learning Models,
  Higher school of economics (HSE) Moscow, Summer School on Machine Leaning in Bioinformatics 2021, online event, August 2021, Invited Talk
• Wojciech Samek
  Toward Explainable AI,
  ICML 2021 Workshop on "Theoretic Foundation, Criticism, and Application Trend of Explainable AI", July 2021, Talk
• Wojciech Samek
  XXAI: eXtending XAI towards Actionable Interpretability,
  IEEE CVPR Workshop on "Interpretable Machine Learning for Computer Vision", online event, June 2021, Talk
• Wojciech Samek
  Explainable AI: Concepts, Methods and Applications,
  2nd Eddy Cross Disciplinary Symposium, online event, June 2021, Talk
• Sebastian Lapuschkin
  Beyond Explaining: Explainable AI for Model Improvement,
  Melanoma Patient Network Europe, MPNE Seminar, online event, June 2021, Invited Talk
• Wojciech Samek
  Recent Advances in Explainable AI,
  HEIBRIDS Lecture Series, online event, May 2021, Talk
• Sebastian Lapuschkin
  Beyond Explaining: Explainable AI for Model Improvement,
  Sensor and Measurement Science International 2021, online event, May 2021, Invited Talk
• Wojciech Samek
  Beyond Visualization: Using XAI for Better Models,
  Huawei Strategy and Technology Workshop, online event, 2021, Talk

2020

• Wojciech Samek
  DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks,
  Workshop on Energy Efficient Machine Learning and Cognitive Computing, online event, December 2020, Talk
• Wojciech Samek
  Distributed Deep Learning: Concepts, Methods & Applications in Wireless Networks,
  IEEE GLOBECOM, Taipei, Taiwan, December 2020, Tutorial, Talk
• Wojciech Samek
  From Local to Global Interpretations of DNNs,
  Workshop on Auditing AI-Systems: From Basics to Applications, Berlin, Germany, October 2020, Talk
• Wojciech Samek
  Extending Explainable AI Beyond Deep Classifiers,
  MICCAI'20 Workshop on "Interpretability of Machine Intelligence in Medical Image Computing", Lima, Peru, October 2020, Talk
• Wojciech Samek
  Recent Advances in XAI,
  ACM CIKM'20 Workshop on "Advances in Machine Learning and Interpretable AI", Galway, Ireland, October 2020, Talk
• Wojciech Samek
  Introduction to Explainable AI,
  International Summer School on Deep Learning, Gdansk, Poland, September 2020, Talk
• Wojciech Samek
  Explainable AI: Basics and Extensions,
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Ghent, Belgium, September 2020, Tutorial, Invited Talk
• Wojciech Samek
  Interpretable and Explainable Deep Learning,
  Summer School on Machine Learning in Bioinformatics, online, August 2020, Talk
• Sebastian Lapuschkin
  Towards Best Practice in Explaining Neural Network Decisions with LRP,
  AI Campus, KI-Campus -- Die Lernplattform für Künstliche Intelligenz, online event, August 2020, Invited Talk
• Wojciech Samek
  A Universal Compression Algorithm for Deep Neural Networks,
  AI for Good Global Summit 2020, Geneva, Switzerland, August 2020, Talk
• Sebastian Lapuschkin
  XAI for Analyzing and Unlearning Spurious Correlations in ImageNet,
  XXAI: Extending Explainable AI Beyond Deep Models and Classifiers ( ICML 2020 Workshop), online event, July 2020, Talk
• Sebastian Lapuschkin
  Towards Best Practice in Explaining Neural Network Decisions with LRP,
  IEEE, IEEE World Congress on Computational Intelligence, online event, July 2020, Talk
• Wojciech Samek, Felix Sattler
  Distributed and Efficient Deep Learning,
  IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, May 2020, Tutorial, Invited Talk
• Wojciech Samek
  Robust and Communication-Efficient Federated Learning,
  Workshop "Sensor AI", Berlin, Germany, April 2020, Talk
• Sebastian Lapuschkin
  Interpretable Machine Learning with Layer-wise Relevance Propagation,
  Fraunhofergesellschaft, FRAUNHOFER-SYMPOSIUM »NETZWERT« 2021, München, February 2020, Invited Talk
• Wojciech Samek
  Explaining the Decisions of Deep Neural Networks and Beyond,
  Oberwolfach Workshop on "Statistics meets Machine Learning", Oberwolfach, Germany, January 2020, Talk
• Wojciech Samek
  Recent Advances in Federated Learning for Communication,
  ITU AI/ML in 5G Challenge, virtual event, 2020, Talk

2019

• Wojciech Samek
  Neuronale Netzwerke beim Denken beobachten,
  Nationales Digital Health Symposium, Berlin, Germany, November 2019, Talk
• Wojciech Samek
  Interpretable & Transparent Deep Learning,
  OpTecBB Workshop on Machine learning in Optical Analytics, Berlin, Germany, November 2019, Talk
• Wojciech Samek
  Explainable AI,
  FUTURAS IN RES Conference, Berlin, Germany, November 2019, Talk
• Wojciech Samek
  Federated Learning and its Applications in Communications,
  AI for 5G & Beyond Day, Berlin, Germany, November 2019, Talk
• Wojciech Samek
  Meta-Explanations, Interpretable Clustering & Other Recent Developments,
  ICCV 2019, Workshop on Interpretating and Explaining Visual AI Models, Seoul, Korea, October 2019, Talk
• Wojciech Samek
  Compression of Deep Neural Networks,
  ITU Workshop, The future of media, Geneva, Switzerland, October 2019, Talk
• Wojciech Samek
  Explainability of Deep Learning,
  9th Nachwuchsakademie Medizintechnik, Berlin, Germany, September 2019, Talk
• Sebastian Lapuschkin
  Explainable Artificial Intelligence -- Opening the Machine Learning Black Box with Layer-wise Relevance Propagation,
  AMA Science, AMA Wissenschaftsrat 2019, Ladenburg, September 2019, Invited Talk
• Wojciech Samek
  Explainable Artificial Intelligence - Methods, Applications & Recent Developments,
  Cross Domain Conference for Machine Learning and Knowledge Extraction, Canterbury, UK, August 2019, Talk
• Sebastian Lapuschkin
  Explainable Artificial Intelligence -- Opening the Machine Learning Black Box with Layer-wise Relevance Propagation,
  Simula, Summer School on Smart cities for a Sustainable Energy Future - From Design to Practice, Berlin, August 2019, Invited Talk
• Wojciech Samek
  Interpreting Deep Neural Networks,
  ICIAM Mini-Symposium on "Theoretical Foundations of Deep Learning", Valencia, Spain, July 2019, Talk
• Wojciech Samek
  Interpretable & Transparent Deep Learning,
  IEEE, Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, July 2019, Tutorial, Invited Talk
• Wojciech Samek
  Deep Understanding of Deep Models,
  Artificial Intelligence Methods in Cosmology Workshop, Ascona, Switzerland, June 2019, Talk
• Wojciech Samek
  Towards Explainable Artificial Intelligence,
  5th Digital Future Science Match, Berlin, Germany, May 2019, Talk
• Wojciech Samek
  Deep Learning: Models, Applications & Challenges,
  Leopoldina Meeting "Digital Pathology on the Boarder to Molecular Imaging", Venice, Italy, March 2019, Talk
• Wojciech Samek
  Convergence of Machine Learning and Communications,
  CIEMI Congress on Intelligent Systems, San Jose, Costa Rica, March 2019, Talk
• Wojciech Samek
  Interpretable Deep Learning,
  Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany, January 2019, Talk
• Wojciech Samek
  Interpreting and Explaining Deep Neural Networks,
  Ecole polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland, January 2019, Talk
• Wojciech Samek
  Interpretable & Transparent Deep Learning,
  Northern Lights Deep Learning Workshop, Tromsø, Norway, January 2019, Talk
• Wojciech Samek
  Opening the Black Box: Making Deep Learning Interpretable & Transparent,
  EPFL, Applied Machine Learning Days, Lausanne, Switzerland, January 2019, Talk

2018

• Wojciech Samek
  Transparent & Interpretable Deep Learning for Health,
  8th Machine Learning in Healthcare Meetup, Berlin, Germany, November 2018, Talk
• Wojciech Samek
  Interpreting and Explaining Deep Neural Networks,
  Columbia University, New York City, USA, November 2018, Talk
• Wojciech Samek
  Interpretable Deep Learning & its Applications in the Neurosciences,
  Max Planck Institute for Human Cognitive and Brain, Leipzig, Germany, October 2018, Talk
• Wojciech Samek
  Interpretable Deep Learning: Towards Understanding & Explaining Deep Neural Networks,
  IEEE International Conference on Image Processing (ICIP), Athens, Kefalonia, Greece, October 2018, Invited Tutorial, Invited Talk
• Wojciech Samek
  Transparent & Trustworthy AI for Medical Applications,
  ITU, Workshop on Artificial Intelligence for Health, Geneva, Switzerland, September 2018, Talk
• Wojciech Samek
  Interpreting Deep Neural Networks by Explaining their Predictions,
  Stanford University, CA, USA, August 2018, Talk
• Wojciech Samek
  Interpreting and Explaining Deep Models in Computer Vision,
  IAPR Summer School on Machine and Visual Intelligence, Vico Equense, Italy, August 2018, Talk
• Wojciech Samek
  Interpretable, Efficient and Distributed Deep Learning,
  Fritz Haber Institute, Seminar, Berlin, Germany, July 2018, Talk
• Wojciech Samek
  Understanding Machine Learning,
  IoT Week 2018 - Making the Data Revolution Happen: Machine Learning to Exploit Big Data, Bilbao, Spain, June 2018, Invited Talk
• Wojciech Samek
  Interpreting and Explaining Deep Models in Computer Vision,
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 2018, Invited Tutorial, Invited Talk
• Wojciech Samek
  How to make the black box of neural networks transparent – the path towards explainable AI,
  AI for Good Global Summit 2018, May 2018, Invited Talk
• Wojciech Samek
  Interpreting Deep Neural Networks and their Predictions,
  2nd IML Machine Learning Workshop, CERN, Geneva, Switzerland, April 2018, Invited Talk
• Wojciech Samek
  Efficient, Distributed and Interpretable Deep Learning,
  ITU Workshop on "Impact of AI on ICT Infrastructures", Xi'an, China, April 2018, Invited Talk
• Wojciech Samek
  Efficient and Interpretable Deep Learning,
  Forum Digital Transformation: The impacts of Artificial Intelligence on Economy, Berlin, Germany, March 2018, Talk
• Wojciech Samek
  Opening the Black Box of Deep Learning,
  11th RDA Plenary - Industry Side Meeting "Towards a Flourishing Data Economy", Berlin, Germany, March 2018, Invited Talk
• Wojciech Samek
  Making Deep Neural Networks Transparent,
  HAP Workshop | Big Data Science in Astroparticle Physics, Aachen, Germany, February 2018, Invited Talk
• Wojciech Samek
  Explaining Deep Neural Network Decisions,
  Deep Learning for Computational Biology Workshop, Berlin, Germany, February 2018, Invited Talk
• Wojciech Samek
  Komplexitätsreduzierte Algorithmen des Maschinellen Lernens,
  Fraunhofer-Symposium "Netzwert", Munich, Germany, February 2018, Invited Talk
• Wojciech Samek
  Interpretable Machine Learning,
  Artificial Intelligence for Practitioners, Berlin, Germany, January 2018, Talk
• Wojciech Samek
  Wie intelligent ist die Künstliche Intelligenz?,
  Hybrid Talks XXIX "Intelligenz", Berlin, Germany, January 2018, Talk
• Wojciech Samek
  Efficient Deep Learning in Communications,
  ITU Workshop on "Machine Learning for 5G and beyond", Geneva, Switzerland, January 2018, Invited Talk
• Wojciech Samek
  Towards Explainable AI,
  HIIG Workshop, Understanding AI and us, Berlin, Germany, 2018, Talk

2017

• Wojciech Samek
  Explaining Neural Networks in the Wild,
  NIPS 2017 Workshop "Interpreting, Explaining and Visualizing Deep Learning - Now what?”, Long Beach, California, USA, December 2017, Talk
• Wojciech Samek
  Towards explainable Deep Learning,
  CoSIP Intense Course on Deep Learning, Berlin, Germany, November 2017, Talk
• Sebastian Lapuschkin
  Understanding and Comparing Deep Neural Networks for Age and Gender Classification,
  IEEE, Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCVW), Venice, Italy, October 2017, Talk
• Wojciech Samek
  Methods for Understanding How Deep Neural Networks Work,
  Embedded Vision Alliance Vision Industry and Technology Forum, Hamburg, Germany, September 2017, Talk
• Wojciech Samek
  Interpretable Machine Learning,
  39th German Conference on Pattern Recognition (GCPR), Basel, Switzerland, September 2017, Tutorial, Talk
• Wojciech Samek
  Interpretable Machine Learning,
  DTU Summer School on Advanced Topics in Machine Learning, Denmark, Copenhagen, Denmark, August 2017, Talk
• Wojciech Samek
  What can we learn from interpreting deep neural networks?,
  Deep Learning: Theory, Algorithms, and Applications, Berlin, Germany, June 2017, Talk
• Wojciech Samek
  Methods for Interpreting and Understanding Deep Neural Networks,
  IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), LA, New Orleans, Louisiana, USA, March 2017, Tutorial, Talk

2016

• Wojciech Samek
  Interpretable Deep Learning,
  Quo Vadis Game Developer Conference, Berlin, Germany, April 2016, Talk
• Wojciech Samek
  Effective Data Analytics,
  Big Data Excellence for Utilities Conference, Berlin, Germany, February 2016, Talk

2015

• Wojciech Samek
  Explaining individual deep network predictions and measuring the quality of these explanations,
  Feature Extraction Workshop: Modern Questions and Challenges, NIPS workshop, Montreal, Canada, December 2015, Talk
• Wojciech Samek
  Divergence-based Spatial Filtering for robust BCI,
  Germany-Japan Adaptive BCI Workshop, Kyoto, Japan, October 2015, Talk
• Wojciech Samek
  The Machine Learning way to Video Analysis and Compression,
  Trends in Video Analysis, Representation and Delivery Workshop, Aachen, Germany, February 2015, Talk

2023

• Ximeng Cheng, Marc Vischer, Zachary Schellin, Leila Arras, Monique Kuglitsch, Wojciech Samek, Jackie Ma
  Explainability in GeoAI,
  In: Handbook of Geospatial Artificial Intelligence, CRC Press, Boca Raton, USA, pp. 177-201, December 2023, doi: 10.1201/9781003308423-9, Book Chapter
• Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek
  FedAUXfdp: Differentially Private One-Shot Federated Distillation,
  In: Trustworthy Federated Learning, Lecture Notes in Computer Science, Springer International Publishing, Cham, Switzerland, vol. 13448, pp. 100-114, March 2023, doi: 10.1007/978-3-031-28996-5_8, Book Chapter
• Wojciech Samek
  Explainable Deep Learning: Methods, Concepts and New Developments,
  In: Explainable Deep Learning AI: Methods and Challenges, Academic Press, , pp. 7-33, 2023, Book Chapter

2022

• Wojciech Samek, Leila Arras, Ahmed Osman, Grégoire Montavon, Klaus-Robert Müller
  Explaining the Decisions of Convolutional and Recurrent Neural Networks,
  In: Mathematical Aspects of Deep Learning, Cambridge University Press, Cambridge, UK, pp. 229–266, November 2022, doi: 10.1017/9781009025096.006, Book Chapter
• Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek
  xxAI - Beyond Explainable AI,
  Lecture Notes in Artificial Intelligence, Springer, Cham, vol. 13200, April 2022, doi: 10.1007/978-3-031-04083-2
• Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin
  ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs,
  In: xxAI - Beyond Explainable AI, LNAI, Springer, Cham, vol. 13200, pp. 271-296, April 2022, doi: 10.1007/978-3-031-04083-2_14, Book Chapter
• Grégoire Montavon, Jacob R. Kauffmann, Wojciech Samek, Klaus-Robert Müller
  Explaining the Predictions of Unsupervised Learning Models,
  In: xxAI - Beyond Explainable AI, LNAI, Springer, Cham, vol. 13200, pp. 117-138, April 2022, doi: 10.1007/978-3-031-04083-2_7, Book Chapter
• Andreas Holzinger, Anna Saranti, Christoph Molnar, Przemyslaw Biecek, Wojciech Samek
  Explainable AI Methods - A Brief Overview,
  In: xxAI - Beyond Explainable AI, LNAI, Springer, Cham, vol. 13200, pp. 13-38, April 2022, doi: 10.1007/978-3-031-04083-2_2, Book Chapter

2019

• Guangtao Zhai, Ke Gu, Jiheng Wang, Wojciech Samek
  Quality Perception of Advanced Multimedia Systems,
  In: Digital Signal Processing, Elsevier Inc., Amsterdam, Netherlands, ISBN: 1051--2004, vol. 91, pp. 1-2, August 2019, doi: 10.1016/j.dsp.2019.05.013, Editorial, Book Chapter
• Wojciech Samek, Klaus-Robert Müller
  Towards Explainable Artificial Intelligence,
  In: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Lecture Notes in Computer Science), Springer International Publishing, Springer Nature Switzerland, ISBN: 978-3-030-28953-9, pp. 5-22, August 2019, doi: 10.1007/978-3-030-28954-6_1, Book Chapter
• Leila Arras, José Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek
  Explaining and Interpreting LSTMs,
  In: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Lecture Notes in Computer Science), Springer International Publishing, Springer Nature Switzerland, ISBN: 978-3-030-28953-9, vol. 11700, pp. 211-238, August 2019, doi: 10.1007/978-3-030-28954-6_11, Book Chapter
• Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller
  Layer-Wise Relevance Propagation: An Overview,
  In: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Lecture Notes in Computer Science), Springer International Publishing, Springer Nature Switzerland, ISBN: 978-3-030-28953-9, vol. 11700, pp. 193-209, August 2019, doi: 10.1007/978-3-030-28954-6_10, Book Chapter
• Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
  Understanding Patch-Based Learning of Video Data by Explaining Predictions,
  In: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Lecture Notes in Computer Science), Springer International Publishing, Springer Nature Switzerland, ISBN: 978-3-030-28953-9, vol. 11700, pp. 297-309, August 2019, doi: 10.1007/978-3-030-28954-6_16, Book Chapter
• Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller
  Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Lecture Notes in Computer Science),
  Springer International Publishing, Springer Nature Switzerland, ISBN: 978-3-030-28953-9, vol. 11700, August 2019, doi: 10.1007/978-3-030-28954-6, Editors
• Sergio Cruces, Rubén Martín-Clemente, Wojciech Samek
  Information Theory Applications in Signal Processing,
  In: special issue of Entropy, MDPI, Basel, Switzerland, vol. 21, p. 653, July 2019, doi: 10.3390/e21070653, Editorial, Book Chapter

2017

• Koh Jing Yu, Wojciech Samek, Klaus-Robert Müller, Alexander Binder
  Object Boundary Detection and Classification with Image-level Labels,
  In: Pattern Recognition - 39th German Conference, GCPR 2017, Lecture Notes in Computer Science, Springer Verlag, Heidelberg, Germany, vol. 10496, pp. 153-164, September 2017, doi: 10.1007/978-3-319-66709-6_13, Book Chapter

2016

• Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  Identifying individual facial expressions by deconstructing a neural network,
  In: Pattern Recognition - 38th German Conference, GCPR 2016, Lecture Notes in Computer Science, Springer Verlag, Heidelberg, Germany, vol. 9796, pp. 344-354, September 2016, doi: 10.1007/978-3-319-45886-1_28, Book Chapter
• Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek
  Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers,
  In: Artificial Neural Networks and Machine Learning – ICANN 2016, Lecture Notes in Computer Science, Springer Verlag, Heidelberg, Germany, vol. 9887, pp. 63-71, August 2016, doi: 10.1007/978-3-319-44781-0_8, Book Chapter
• Alexander Binder, Sebastian Bach, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
  Layer-wise Relevance Propagation for Deep Neural Network Architectures,
  In: Information Science and Applications (ICISA) 2016, Lecture Notes in Electrical Engineering, Springer Verlag, Singapore, vol. 376, pp. 913-922, February 2016, doi: 10.1007/978-981-10-0557-2_87, Book Chapter

2015

• Wojciech Samek
  Über die robuste räumliche Filterung von EEG in nichtstationären Umgebungen,
  In: Steffen Hölldobler et al. (Editors), Ausgezeichnete Informatikdissertationen 2014, GI-Edition - Lecture Notes in Informatics (LNI), Köllen Verlag, Bonn, pp. 251-260, January 2015, Book Chapter

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