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, doi: 10.1109/TMTT.2025.3557081
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
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
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
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
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