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
• Domenico Vitali, Alessandro Chillico, Wojciech Samek, Olof Bengtsson
  Improved On-Wafer Probing of High Frequency Components Based on Optical Recognition of the Probe Positions,
  IEEE Transactions on Microwave Theory and Techniques, March 2025
• 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
• 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

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
• 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
• 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
• 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

2023

• 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
• 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
• 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
• 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
• 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

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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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

• 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
• 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
• 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

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
• 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
• 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

2018

• 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
• 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

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

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
• 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
• 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

• 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

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
• Sonia Joseph, Praneet Suresh, Ethan Goldfarb, Lorenz Hufe, Yossi Gandelsman, Robert Graham, Danilo Bzdok, Wojciech Samek, Blake Aaron Richards
  Steering CLIP's Vision Transformer with Sparse Autoencoders,
  IEEE CVPR Workshop on "Mechanistic Interpretability for Vision", Nashville, TN, USA, 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
• 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
• 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
• 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
• 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
• 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
• 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

2021

• 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
• 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
• 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

• 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
• 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
• 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

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

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
• 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
• 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
• 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 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 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
• 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

• 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
• 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

2019

• Wojciech Samek, Vignesh Srinivasan, Luis Oala, Thomas Wiegand
  Robustness - Safety and reliability in AI4H,
  FG-AI4H-E-025, Geneva, Switzerland, May 2019

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
  Component-level Explanation and Validation of AI Models,
  6th International Conference on Deep Learning Theory and Applications, Bilbao, Spain, June 2025, Talk
• 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
  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
  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
• 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
  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
• 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
• 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

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
  Meta-Explanations, Interpretable Clustering & Other Recent Developments,
  ICCV 2019, Workshop on Interpretating and Explaining Visual AI Models, Seoul, Korea, 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
  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 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
  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
  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

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

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
• 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

• 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

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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