A Hybrid Supervised-Unsupervised Vocabulary Generation Algorithm for Visual Concept Recognition. - Alexander Binder; Wojciech Wojcikiewicz; Christina Müller; Motoaki Kawanabe (ACCV (3), 2010)

Shrinking large visual vocabularies using multi-label agglomerative information bottleneck. - Wojciech Wojcikiewicz; Alexander Binder; Motoaki Kawanabe (ICIP, 2010)

Enhancing Image Classification with Class-wise Clustered Vocabularies. - Wojciech Wojcikiewicz; Alexander Binder; Motoaki Kawanabe (ICPR, 2010)

Multi-task Learning via Non-sparse Multiple Kernel Learning. - Wojciech Samek; Alexander Binder; Motoaki Kawanabe (CAIP (1), 2011)

The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task. - Alexander Binder; Wojciech Samek; Marius Kloft; Christina Müller; Klaus-Robert Müller; Motoaki Kawanabe (CLEF (Notebook Papers/Labs/Workshop), 2011)

Improving Classification Performance of BCIs by Using Stationary Common Spatial Patterns and Unsupervised Bias Adaptation. - Wojciech Wojcikiewicz; Carmen Vidaurre; Motoaki Kawanabe (HAIS (2), 2011)

An Information Geometrical View of Stationary Subspace Analysis. - Motoaki Kawanabe; Wojciech Samek; Paul von Bünau; Frank C. Meinecke (ICANN (2), 2011)

Stationary Common Spatial Patterns: Towards robust classification of non-stationary EEG signals. - Wojciech Wojcikiewicz; Carmen Vidaurre; Motoaki Kawanabe (ICASSP, 2011)

Multi-modal visual concept classification of images via Markov random walk over tags. - Motoaki Kawanabe; Alexander Binder; Christina Müller; Wojciech Wojcikiewicz (WACV, 2011)

Insights from Classifying Visual Concepts with Multiple Kernel Learning - Alexander Binder; Shinichi Nakajima; Marius Kloft; Christina Müller; Wojciech Samek; Ulf Brefeld; Klaus-Robert Müller; Motoaki Kawanabe (CoRR, 2011)

Brain-computer interfacing in discriminative and stationary subspaces. - Wojciech Samek; Klaus-Robert Müller; Motoaki Kawanabe; Carmen Vidaurre (EMBC, 2012)

Multiple Kernel Learning for Brain-Computer Interfacing. - Wojciech Samek; Alexander Binder; Klaus-Robert Müller (EMBC, 2013)

Robust Spatial Filtering with Beta Divergence. - Wojciech Samek; Duncan A. J. Blythe; Klaus-Robert Müller; Motoaki Kawanabe (NIPS, 2013)

Enhanced representation and multi-task learning for image annotation. - Alexander Binder; Wojciech Samek; Klaus-Robert Müller; Motoaki Kawanabe (Comput. Vis. Image Underst., 2013)

Transferring Subspaces Between Subjects in Brain-Computer Interfacing. - Wojciech Samek; Frank C. Meinecke; Klaus-Robert Müller (IEEE Trans. Biomed. Eng., 2013)

Information geometry meets BCI spatial filtering using divergences. - Wojciech Samek; Klaus-Robert Müller (BCI, 2014)

Über die robuste räumliche Filterung von EEG in nichtstationären Umgebungen. - Wojciech Samek (Ausgezeichnete Informatikdissertationen, 2014)

Robust common spatial patterns by minimum divergence covariance estimator. - Wojciech Samek; Motoaki Kawanabe (ICASSP, 2014)

Robust Common Spatial Filters with a Maxmin Approach. - Motoaki Kawanabe; Wojciech Samek; Klaus-Robert Müller; Carmen Vidaurre (Neural Comput., 2014)

On robust spatial filtering of EEG in nonstationary environments. - Wojciech Samek (2014)

Machine Learning for Visual Concept Recognition and Ranking for Images. - Alexander Binder; Wojciech Samek; Klaus-Robert Müller; Motoaki Kawanabe (Towards the Internet of Services, 2014)

Robust common spatial patterns based on Bhattacharyya distance and Gamma divergence. - Stephanie Brandl; Klaus-Robert Müller; Wojciech Samek (BCI, 2015)

Investigating effects of different artefact types on motor imagery BCI. - Laura Frølich; Irene Winkler; Klaus-Robert Müller; Wojciech Samek (EMBC, 2015)

Tackling noise, artifacts and nonstationarity in BCI with robust divergences. - Wojciech Samek; Klaus-Robert Müller (EUSIPCO, 2015)

Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment. - Stephanie Brandl; Johannes Höhne; Klaus-Robert Müller; Wojciech Samek (NER, 2015)

Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data. - Sven Dähne; Felix Bießmann; Wojciech Samek; Stefan Haufe; Dominique Goltz; Christopher Gundlach; Arno Villringer; Siamac Fazli; Klaus-Robert Müller (Proc. IEEE, 2015)

Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain-Computer Interfaces. - Siamac Fazli; Sven Dähne; Wojciech Samek; Felix Bießmann; Klaus-Robert Müller (Proc. IEEE, 2015)

Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. - Sebastian Lapuschkin; Alexander Binder; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CVPR, 2016)

Identifying Individual Facial Expressions by Deconstructing a Neural Network. - Farhad Arbabzadah; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (GCPR, 2016)

On the robustness of action recognition methods in compressed and pixel domain. - Vignesh Srinivasan; Serhan Gul; Sebastian Bosse; Jan Timo Meyer; Thomas Schierl; Cornelius Hellge; Wojciech Samek (EUVIP, 2016)

Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. - Alexander Binder; Grégoire Montavon; Sebastian Lapuschkin; Klaus-Robert Müller; Wojciech Samek (ICANN (2), 2016)

Controlling explanatory heatmap resolution and semantics via decomposition depth. - Sebastian Bach; Alexander Binder; Klaus-Robert Müller; Wojciech Samek (ICIP, 2016)

Shearlet-based reduced reference image quality assessment. - Sebastian Bosse; Qiaobo Chen; Mischa Siekmann; Wojciech Samek; Thomas Wiegand 001 (ICIP, 2016)

A deep neural network for image quality assessment. - Sebastian Bosse; Dominique Maniry; Thomas Wiegand 001; Wojciech Samek (ICIP, 2016)

Quality assessment of image patches distorted by image compression using crowdsourcing. - Sebastian Bosse; Mischa Siekmann; Jennifer Rasch; Thomas Wiegand 001; Wojciech Samek (ICME, 2016)

Hybrid video object tracking in H.265/HEVC video streams. - Serhan Gul; Jan Timo Meyer; Cornelius Hellge; Thomas Schierl; Wojciech Samek (MMSP, 2016)

Neural network-based full-reference image quality assessment. - Sebastian Bosse; Dominique Maniry; Klaus-Robert Müller; Thomas Wiegand 001; Wojciech Samek (PCS, 2016)

Explaining Predictions of Non-Linear Classifiers in NLP. - Leila Arras; Franziska Horn; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (Rep4NLP@ACL, 2016)

Brain-Computer Interfacing for multimedia quality assessment. - Sebastian Bosse; Klaus-Robert Müller; Thomas Wiegand 001; Wojciech Samek (SMC, 2016)

Alternative CSP approaches for multimodal distributed BCI data. - Stephanie Brandl; Klaus-Robert Müller; Wojciech Samek (SMC, 2016)

"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach. - Leila Arras; Franziska Horn; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CoRR, 2016)

Zero Shot Learning for Semantic Boundary Detection - How Far Can We Get? - Jing Yu Koh; Wojciech Samek; Klaus-Robert Müller; Alexander Binder (CoRR, 2016)

Sharing Hash Codes for Multiple Purposes. - Wikor Pronobis; Danny Panknin; Johannes Kirschnick; Vignesh Srinivasan; Wojciech Samek; Volker Markl; Manohar Kaul; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2016)

Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. - Wojciech Samek; Grégoire Montavon; Alexander Binder; Sebastian Lapuschkin; Klaus-Robert Müller (CoRR, 2016)

Interpretable Deep Neural Networks for Single-Trial EEG Classification. - Irene Sturm; Sebastian Bach; Wojciech Samek; Klaus-Robert Müller (CoRR, 2016)

On robust spatial filtering of EEG in nonstationary environments. - Wojciech Samek (it Inf. Technol., 2016)

The LRP Toolbox for Artificial Neural Networks. - Sebastian Lapuschkin; Alexander Binder; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (J. Mach. Learn. Res., 2016)

Multiscale temporal neural dynamics predict performance in a complex sensorimotor task. - Wojciech Samek; Duncan A. J. Blythe; Gabriel Curio; Klaus-Robert Müller; Benjamin Blankertz; Vadim V. Nikulin (NeuroImage, 2016)

Object Boundary Detection and Classification with Image-Level Labels. - Jing Yu Koh; Wojciech Samek; Klaus-Robert Müller; Alexander Binder (GCPR, 2017)

Quality assessment of 3D visualizations with vertical disparity: An ERP approach. - Forooz Shahbazi Avarvand; Sebastian Bosse; Guido Nolte; Thomas Wiegand 001; Wojciech Samek (EMBC, 2017)

Measuring the Quality of 3D Visualizations using EEG: a Time-frequency Approach. - Forooz Shahbazi Avarvand; Sebastian Bosse; Guido Nolte; Thomas Wiegand 001; Wojciech Samek (GBCIC, 2017)

Interpretable human action recognition in compressed domain. - Vignesh Srinivasan; Sebastian Lapuschkin; Cornelius Hellge; Klaus-Robert Müller; Wojciech Samek (ICASSP, 2017)

Estimating Position & Velocity in 3D Space from Monocular Video Sequences Using a Deep Neural Network. - Arturo Marbán; Vignesh Srinivasan; Wojciech Samek; Josep Fernández; Alicia Casals (ICCV Workshops, 2017)

Understanding and Comparing Deep Neural Networks for Age and Gender Classification. - Wojciech Samek; Alexander Binder; Sebastian Lapuschkin; Klaus-Robert Müller (ICCV Workshops, 2017)

A perceptually relevant shearlet-based adaptation of the PSNR. - Sebastian Bosse; Mischa Siekmann; Wojciech Samek; Thomas Wiegand 001 (ICIP, 2017)

Detection of Face Morphing Attacks by Deep Learning. - Clemens Seibold; Wojciech Samek; Anna Hilsmann; Peter Eisert (IWDW, 2017)

Explaining Recurrent Neural Network Predictions in Sentiment Analysis. - Leila Arras; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (WASSA@EMNLP, 2017)

Exploring text datasets by visualizing relevant words. - Franziska Horn; Leila Arras; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CoRR, 2017)

Discovering topics in text datasets by visualizing relevant words. - Franziska Horn; Leila Arras; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CoRR, 2017)

Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. - Wojciech Samek; Thomas Wiegand 001; Klaus-Robert Müller (CoRR, 2017)

The Convergence of Machine Learning and Communications. - Wojciech Samek; Slawomir Stanczak; Thomas Wiegand 001 (CoRR, 2017)

Explaining nonlinear classification decisions with deep Taylor decomposition. - Grégoire Montavon; Sebastian Lapuschkin; Alexander Binder; Wojciech Samek; Klaus-Robert Müller (Pattern Recognit., 2017)

Evaluating the Visualization of What a Deep Neural Network Has Learned. - Wojciech Samek; Alexander Binder; Grégoire Montavon; Sebastian Lapuschkin; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2017)

Machine Learning for Early HARQ Feedback Prediction in 5G. - Nils Strodthoff; Baris Göktepe; Thomas Schierl; Wojciech Samek; Cornelius Hellge (GLOBECOM Workshops, 2018)

Transferring Information Between Neural Networks. - Christopher Ehmann; Wojciech Samek (ICASSP, 2018)

Neural Network-Based Estimation of Distortion Sensitivity for Image Quality Prediction. - Sebastian Bosse; Sören Becker 001; Zacharias V. Fisches; Wojciech Samek; Thomas Wiegand 001 (ICIP, 2018)

Estimation of Interaction Forces in Robotic Surgery using a Semi-Supervised Deep Neural Network Model. - Arturo Marbán; Vignesh Srinivasan; Wojciech Samek; Josep Fernández; Alicia Casals (IROS, 2018)

On the Stimulation Frequency in SSVEP-based Image Quality Assessment. - Sebastian Bosse; Milena T. Bagdasarian; Wojciech Samek; Gabriel Curio; Thomas Wiegand 001 (QoMEX, 2018)

Dual Recurrent Attention Units for Visual Question Answering. - Ahmed Osman; Wojciech Samek (CoRR, 2018)

Counterstrike: Defending Deep Learning Architectures Against Adversarial Samples by Langevin Dynamics with Supervised Denoising Autoencoder. - Vignesh Srinivasan; Arturo Marbán; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (CoRR, 2018)

Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks. - Clemens Seibold; Wojciech Samek; Anna Hilsmann; Peter Eisert (CoRR, 2018)

Understanding Patch-Based Learning by Explaining Predictions. - Christopher J. Anders; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (CoRR, 2018)

Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals. - Sören Becker 001; Marcel Ackermann 001; Sebastian Lapuschkin; Klaus-Robert Müller; Wojciech Samek (CoRR, 2018)

What is Unique in Individual Gait Patterns? Understanding and Interpreting Deep Learning in Gait Analysis. - Fabian Horst; Sebastian Lapuschkin; Wojciech Samek; Klaus-Robert Müller; Wolfgang Immanuel Schöllhorn (CoRR, 2018)

Interpretable LSTMs For Whole-Brain Neuroimaging Analyses. - Armin W. Thomas; Hauke R. Heekeren; Klaus-Robert Müller; Wojciech Samek (CoRR, 2018)

Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography. - Tatiana A. Bubba; Gitta Kutyniok; Matti Lassas; Maximilian März; Wojciech Samek; Samuli Siltanen; Vignesh Srinivasan (CoRR, 2018)

Methods for interpreting and understanding deep neural networks. - Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (Digit. Signal Process., 2018)

Wasserstein Stationary Subspace Analysis. - Stephan Kaltenstadler; Shinichi Nakajima; Klaus-Robert Müller; Wojciech Samek (IEEE J. Sel. Top. Signal Process., 2018)

Localizing bicoherence from EEG and MEG. - Forooz Shahbazi Avarvand; Sarah Bartz; Christina Andreou; Wojciech Samek; Gregor Leicht; Christoph Mulert; Andreas K. Engel; Guido Nolte (NeuroImage, 2018)

Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition. - Sebastian Bosse; Laura Acqualagna; Wojciech Samek; Anne K. Porbadnigk; Gabriel Curio; Benjamin Blankertz; Klaus-Robert Müller; Thomas Wiegand 001 (IEEE Trans. Circuits Syst. Video Technol., 2018)

Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment. - Sebastian Bosse; Dominique Maniry; Klaus-Robert Müller; Thomas Wiegand 001; Wojciech Samek (IEEE Trans. Image Process., 2018)

Viewport Forecasting in 360° Virtual Reality Videos with Machine Learning. - Johanna Vielhaben; Hüseyin Camalan; Wojciech Samek; Markus Wenzel 002 (AIVR, 2019)

Evaluating Recurrent Neural Network Explanations. - Leila Arras; Ahmed Osman; Klaus-Robert Müller; Wojciech Samek (BlackboxNLP@ACL, 2019)

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training. - Jan Laermann; Wojciech Samek; Nils Strodthoff (GCPR, 2019)

Rotation Invariant Clustering of 3D Cell Nuclei Shapes. - Patrick Wagner 002; Jakob Paul Morath; Arturo Zychlinsky; Klaus-Robert Müller; Wojciech Samek (EMBC, 2019)

Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. - Vignesh Srinivasan; Ercan E. Kuruoglu; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (EUSIPCO, 2019)

Multi-Kernel Prediction Networks for Denoising of Burst Images. - Talmaj Marinc; Vignesh Srinivasan; Serhan Gül; Cornelius Hellge; Wojciech Samek (ICIP, 2019)

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. - Felix Sattler; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (IJCNN, 2019)

Entropy-Constrained Training of Deep Neural Networks. - Simon Wiedemann; Arturo Marbán; Klaus-Robert Müller; Wojciech Samek (IJCNN, 2019)

Deep Transfer Learning for Whole-Brain FMRI Analyses. - Armin W. Thomas; Klaus-Robert Müller; Wojciech Samek (OR/MLCN@MICCAI, 2019)

A recurrent convolutional neural network approach for sensorless force estimation in robotic surgery. - Arturo Marbán; Vignesh Srinivasan; Wojciech Samek; Josep Fernández; Alicia Casals (Biomed. Signal Process. Control., 2019)

Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. - Sebastian Lapuschkin; Stephan Wäldchen; Alexander Binder; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (CoRR, 2019)

Robust and Communication-Efficient Federated Learning from Non-IID Data. - Felix Sattler; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (CoRR, 2019)

Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling. - Kim Nicoli; Pan Kessel; Nils Strodthoff; Wojciech Samek; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2019)

DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression. - Simon Wiedemann; Heiner Kirchhoffer; Stefan Matlage; Paul Haase; Arturo Marbán; Talmaj Marinc; David Neumann; Ahmed Osman; Detlev Marpe; Heiko Schwarz; Thomas Wiegand 001; Wojciech Samek (CoRR, 2019)

From Clustering to Cluster Explanations via Neural Networks. - Jacob R. Kauffmann; Malte Esders; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (CoRR, 2019)

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. - Simon Wiedemann; Heiner Kirchhoffer; Stefan Matlage; Paul Haase; Arturo Marbán; Talmaj Marinc; David Neumann; Tung Nguyen 001; Ahmed Osman; Detlev Marpe; Heiko Schwarz; Thomas Wiegand 001; et al. (CoRR, 2019)

Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. - Miriam Hägele; Philipp Seegerer; Sebastian Lapuschkin; Michael Bockmayr; Wojciech Samek; Frederick Klauschen; Klaus-Robert Müller; Alexander Binder (CoRR, 2019)

Towards Explainable Artificial Intelligence. - Wojciech Samek; Klaus-Robert Müller (CoRR, 2019)

Explaining and Interpreting LSTMs. - Leila Arras; Jose A. Arjona-Medina; Michael Widrich; Grégoire Montavon; Michael Gillhofer; Klaus-Robert Müller; Sepp Hochreiter; Wojciech Samek (CoRR, 2019)

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints. - Felix Sattler; Klaus-Robert Müller; Wojciech Samek (CoRR, 2019)

Asymptotically Unbiased Generative Neural Sampling. - Kim A. Nicoli; Shinichi Nakajima; Nils Strodthoff; Wojciech Samek; Klaus-Robert Müller; Pan Kessel (CoRR, 2019)

On the Understanding and Interpretation of Machine Learning Predictions in Clinical Gait Analysis Using Explainable Artificial Intelligence. - Fabian Horst; Djordje Slijepcevic; Sebastian Lapuschkin; Anna-Maria Raberger; Matthias Zeppelzauer; Wojciech Samek; Christian Breiteneder; Wolfgang Immanuel Schöllhorn; Brian Horsak (CoRR, 2019)

Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning. - Seul-Ki Yeom; Philipp Seegerer; Sebastian Lapuschkin; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (CoRR, 2019)

Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed. - Christopher J. Anders; Talmaj Marinc; David Neumann; Wojciech Samek; Klaus-Robert Müller; Sebastian Lapuschkin (CoRR, 2019)

DRAU: Dual Recurrent Attention Units for Visual Question Answering. - Ahmed Osman; Wojciech Samek (Comput. Vis. Image Underst., 2019)

Estimation of distortion sensitivity for visual quality prediction using a convolutional neural network. - Sebastian Bosse; Sören Becker 001; Klaus-Robert Müller; Wojciech Samek; Thomas Wiegand 001 (Digit. Signal Process., 2019)

Quality perception of advanced multimedia systems. - Guangtao Zhai; Ke Gu 001; Jiheng Wang; Wojciech Samek (Digit. Signal Process., 2019)

Information Theory Applications in Signal Processing. - Sergio Cruces; Rubén Martín-Clemente; Wojciech Samek (Entropy, 2019)

iNNvestigate Neural Networks! - Maximilian Alber; Sebastian Lapuschkin; Philipp Seegerer; Miriam Hägele; Kristof T. Schütt; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller; Sven Dähne; Pieter-Jan Kindermans (J. Mach. Learn. Res., 2019)

Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G. - Nils Strodthoff; Baris Göktepe; Thomas Schierl; Cornelius Hellge; Wojciech Samek (IEEE J. Sel. Areas Commun., 2019)

Understanding Patch-Based Learning of Video Data by Explaining Predictions. - Christopher J. Anders; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (Explainable AI, 2019)

Explaining and Interpreting LSTMs. - Leila Arras; Jose A. Arjona-Medina; Michael Widrich; Grégoire Montavon; Michael Gillhofer; Klaus-Robert Müller; Sepp Hochreiter; Wojciech Samek (Explainable AI, 2019)

Layer-Wise Relevance Propagation: An Overview. - Grégoire Montavon; Alexander Binder; Sebastian Lapuschkin; Wojciech Samek; Klaus-Robert Müller (Explainable AI, 2019)

Towards Explainable Artificial Intelligence. - Wojciech Samek; Klaus-Robert Müller (Explainable AI, 2019)

Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. - Vignesh Srinivasan; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (AAAI, 2020)

Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). - Arturo Marbán; Daniel Becking; Simon Wiedemann; Wojciech Samek (CVPR Workshops, 2020)

Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. - Simon Wiedemann; Temesgen Mehari; Kevin Kepp; Wojciech Samek (CVPR Workshops, 2020)

On the Byzantine Robustness of Clustered Federated Learning. - Felix Sattler; Klaus-Robert Müller; Thomas Wiegand 001; Wojciech Samek (ICASSP, 2020)

Dependent Scalar Quantization For Neural Network Compression. - Paul Haase; Heiko Schwarz; Heiner Kirchhoffer; Simon Wiedemann; Talmaj Marinc; Arturo Marbán; Karsten Müller 001; Wojciech Samek; Detlev Marpe; Thomas Wiegand 001 (ICIP, 2020)

Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates. - David Neumann; Felix Sattler; Heiner Kirchhoffer; Simon Wiedemann; Karsten Müller 001; Heiko Schwarz; Thomas Wiegand 001; Detlev Marpe; Wojciech Samek (ICIP, 2020)

ECQ x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. - Daniel Becking; Maximilian Dreyer; Wojciech Samek; Karsten Müller 001; Sebastian Lapuschkin (xxAI@ICML, 2020)

xxAI - Beyond Explainable Artificial Intelligence. - Andreas Holzinger; Randy Goebel; Ruth Fong; Taesup Moon; Klaus-Robert Müller; Wojciech Samek (xxAI@ICML, 2020)

Explainable AI Methods - A Brief Overview. - Andreas Holzinger; Anna Saranti; Christoph Molnar; Przemyslaw Biecek; Wojciech Samek (xxAI@ICML, 2020)

Explaining the Predictions of Unsupervised Learning Models. - Grégoire Montavon; Jacob R. Kauffmann; Wojciech Samek; Klaus-Robert Müller (xxAI@ICML, 2020)

Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. - Gary S. W. Goh; Sebastian Lapuschkin; Leander Weber; Wojciech Samek; Alexander Binder (ICPR, 2020)

Explanation-Guided Training for Cross-Domain Few-Shot Classification. - Jiamei Sun; Sebastian Lapuschkin; Wojciech Samek; Yunqing Zhao; Ngai-Man Cheung; Alexander Binder (ICPR, 2020)

Towards Best Practice in Explaining Neural Network Decisions with LRP. - Maximilian Kohlbrenner; Alexander Bauer 001; Shinichi Nakajima; Alexander Binder; Wojciech Samek; Sebastian Lapuschkin (IJCNN, 2020)

UDSMProt: universal deep sequence models for protein classification. - Nils Strodthoff; Patrick Wagner 002; Markus Wenzel 002; Wojciech Samek (Bioinform., 2020)

USMPep: universal sequence models for major histocompatibility complex binding affinity prediction. - Johanna Vielhaben; Markus Wenzel 002; Wojciech Samek; Nils Strodthoff (BMC Bioinform., 2020)

Understanding Image Captioning Models beyond Visualizing Attention. - Jiamei Sun; Sebastian Lapuschkin; Wojciech Samek; Alexander Binder (CoRR, 2020)

Trends and Advancements in Deep Neural Network Communication. - Felix Sattler; Thomas Wiegand 001; Wojciech Samek (CoRR, 2020)

Towards Ground Truth Evaluation of Visual Explanations. - Ahmed Osman; Leila Arras; Wojciech Samek (CoRR, 2020)

Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. - Wojciech Samek; Grégoire Montavon; Sebastian Lapuschkin; Christopher J. Anders; Klaus-Robert Müller (CoRR, 2020)

Interval Neural Networks: Uncertainty Scores. - Luis Oala; Cosmas Heiss; Jan MacDonald; Maximilian März; Wojciech Samek; Gitta Kutyniok (CoRR, 2020)

MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures. - Saúl Calderón Ramírez; Luis Oala; Jordina Torrents-Barrena; Shengxiang Yang; Armaghan Moemeni; Wojciech Samek; Miguel A. Molina-Cabello (CoRR, 2020)

Sensor Artificial Intelligence and its Application to Space Systems - A White Paper. - Anko Börner; Heinz-Wilhelm Hübers; Odej Kao; Florian Schmidt 006; Soeren Becker 001; Joachim Denzler; Daniel Matolin; David Haber; Sergio Lucia; Wojciech Samek; Rudolph Triebel; Sascha Eichstädt; et al. (CoRR, 2020)

Langevin Cooling for Domain Translation. - Vignesh Srinivasan; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (CoRR, 2020)

Communication-Efficient Federated Distillation. - Felix Sattler; Arturo Marbán; Roman Rischke; Wojciech Samek (CoRR, 2020)

Accurate and robust neural networks for face morphing attack detection. - Clemens Seibold; Wojciech Samek; Anna Hilsmann; Peter Eisert (J. Inf. Secur. Appl., 2020)

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. - Simon Wiedemann; Heiner Kirchhoffer; Stefan Matlage; Paul Haase; Arturo Marbán; Talmaj Marinc; David Neumann; Tung Nguyen 001; Heiko Schwarz; Thomas Wiegand 001; Detlev Marpe; Wojciech Samek (IEEE J. Sel. Top. Signal Process., 2020)

Learning with explainable trees. - Wojciech Samek (Nat. Mach. Intell., 2020)

Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements. - Felix Sattler; Jackie Ma; Patrick Wagner 002; David Neumann; Markus Wenzel 002; Ralf Schäfer; Wojciech Samek; Klaus-Robert Müller; Thomas Wiegand 001 (npj Digit. Medicine, 2020)

Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. - Felix Sattler; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (IEEE Trans. Neural Networks Learn. Syst., 2020)

Compact and Computationally Efficient Representation of Deep Neural Networks. - Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (IEEE Trans. Neural Networks Learn. Syst., 2020)

Interval Neural Networks as Instability Detectors for Image Reconstructions. - Jan MacDonald; Maximilian März; Luis Oala; Wojciech Samek (Bildverarbeitung für die Medizin, 2021)

Encoder Optimizations For The NNR Standard On Neural Network Compression. - Paul Haase; Daniel Becking; Heiner Kirchhoffer; Karsten Müller 001; Heiko Schwarz; Wojciech Samek; Detlev Marpe; Thomas Wiegand 001 (ICIP, 2021)

Detecting failure modes in image reconstructions with interval neural network uncertainty. - Luis Oala; Cosmas Heiß; Jan MacDonald; Maximilian März; Gitta Kutyniok; Wojciech Samek (Int. J. Comput. Assist. Radiol. Surg., 2021)

Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy. - Christopher J. Anders; David Neumann; Wojciech Samek; Klaus-Robert Müller; Sebastian Lapuschkin (CoRR, 2021)

On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. - Vignesh Srinivasan; Nils Strodthoff; Jackie Ma; Alexander Binder; Klaus-Robert Müller; Wojciech Samek (CoRR, 2021)

Reward-Based 1-bit Compressed Federated Distillation on Blockchain. - Leon Witt; Usama Zafar; KuoYeh Shen; Felix Sattler; Dan Li 001; Wojciech Samek (CoRR, 2021)

Toward Explainable AI for Regression Models. - Simon Letzgus; Patrick Wagner 002; Jonas Lederer; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (CoRR, 2021)

Machine Learning for Health: Algorithm Auditing & Quality Control. - 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; et al. (J. Medical Syst., 2021)

Robustifying models against adversarial attacks by Langevin dynamics. - Vignesh Srinivasan; Csaba Rohrer; Arturo Marbán; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (Neural Networks, 2021)

FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4Bit-Compact Multilayer Perceptrons. - Simon Wiedemann; Suhas Shivapakash; Daniel Becking; Pablo Wiedemann; Wojciech Samek; Friedel Gerfers; Thomas Wiegand 001 (IEEE Open J. Circuits Syst., 2021)

A Unifying Review of Deep and Shallow Anomaly Detection. - Lukas Ruff; Jacob R. Kauffmann; Robert A. Vandermeulen; Grégoire Montavon; Wojciech Samek; Marius Kloft; Thomas G. Dietterich; Klaus-Robert Müller (Proc. IEEE, 2021)

Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. - Wojciech Samek; Grégoire Montavon; Sebastian Lapuschkin; Christopher J. Anders; Klaus-Robert Müller (Proc. IEEE, 2021)

Pruning by explaining: A novel criterion for deep neural network pruning. - Seul-Ki Yeom; Philipp Seegerer; Sebastian Lapuschkin; Alexander Binder; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (Pattern Recognit., 2021)

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. - Nils Strodthoff; Patrick Wagner 002; Tobias Schaeffter; Wojciech Samek (IEEE J. Biomed. Health Informatics, 2021)

Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints. - Felix Sattler; Klaus-Robert Müller; Wojciech Samek (IEEE Trans. Neural Networks Learn. Syst., 2021)

Deep Learning for Whole-Brain Cognitive Decoding. - Klaus-Robert Müller; Armin W. Thomas; Wojciech Samek (BCI, 2022)

Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI. - Sami Ede; Serop Baghdadlian; Leander Weber; An Nguyen; Dario Zanca; Wojciech Samek; Sebastian Lapuschkin (CD-MAKE, 2022)

Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning. - Daniel Becking; Heiner Kirchhoffer; Gerhard Tech; Paul Haase; Karsten Müller 001; Heiko Schwarz; Wojciech Samek (CVPR Workshops, 2022)

History Dependent Significance Coding for Incremental Neural Network Compression. - Gerhard Tech; Paul Haase; Daniel Becking; Heiner Kirchhoffer; Karsten Müller 001; Jonathan Pfaff; Heiko Schwarz; Wojciech Samek; Detlev Marpe; Thomas Wiegand 001 (ICIP, 2022)

FedAUXfdp: Differentially Private One-Shot Federated Distillation. - Haley Hoech; Roman Rischke; Karsten Müller 001; Wojciech Samek (FL@IJCAI, 2022)

PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging. - Frederik Pahde; Leander Weber; Christopher J. Anders; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2022)

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations. - Anna Hedström; Leander Weber; Dilyara Bareeva; Franz Motzkus; Wojciech Samek; Sebastian Lapuschkin; Marina M.-C. Höhne (CoRR, 2022)

From "Where" to "What": Towards Human-Understandable Explanations through Concept Relevance Propagation. - Reduan Achtibat; Maximilian Dreyer; Ilona Eisenbraun; Sebastian Bosse; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2022)

Data Models for Dataset Drift Controls in Machine Learning With Images. - Luis Oala; Marco Aversa; Gabriel Nobis; Kurt Willis; Yoan Neuenschwander; Michèle Buck; Christian Matek; Jérôme Extermann; Enrico Pomarico; Wojciech Samek; Roderick Murray-Smith; Christoph Clausen; et al. (CoRR, 2022)

Explaining automated gender classification of human gait. - Fabian Horst; Djordje Slijepcevic; Matthias Zeppelzauer; Anna-Maria Raberger; Sebastian Lapuschkin; Wojciech Samek; Wolfgang Immanuel Schöllhorn; Christian Breiteneder; Brian Horsak (CoRR, 2022)

Explaining machine learning models for age classification in human gait analysis. - Djordje Slijepcevic; Fabian Horst; Marvin Simak; Sebastian Lapuschkin; Anna-Maria Raberger; Wojciech Samek; Christian Breiteneder; Wolfgang Immanuel Schöllhorn; Matthias Zeppelzauer; Brian Horsak (CoRR, 2022)

Explaining Machine Learning Models for Clinical Gait Analysis. - Djordje Slijepcevic; Fabian Horst; Sebastian Lapuschkin; Brian Horsak; Anna-Maria Raberger; Andreas Kranzl; Wojciech Samek; Christian Breiteneder; Wolfgang Immanuel Schöllhorn; Matthias Zeppelzauer (ACM Trans. Comput. Heal., 2022)

Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. - Christopher J. Anders; Leander Weber; David Neumann; Wojciech Samek; Klaus-Robert Müller; Sebastian Lapuschkin (Inf. Fusion, 2022)

CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations. - Leila Arras; Ahmed Osman; Wojciech Samek (Inf. Fusion, 2022)

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence. - Andreas Holzinger; Matthias Dehmer; Frank Emmert-Streib; Rita Cucchiara; Isabelle Augenstein; Javier Del Ser; Wojciech Samek; Igor Jurisica; Natalia Díaz Rodríguez (Inf. Fusion, 2022)

Explain and improve: LRP-inference fine-tuning for image captioning models. - Jiamei Sun; Sebastian Lapuschkin; Wojciech Samek; Alexander Binder (Inf. Fusion, 2022)

Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. - Simon M. Hofmann; Frauke Beyer; Sebastian Lapuschkin; Ole Goltermann; Markus Loeffler; Klaus-Robert Müller; Arno Villringer; Wojciech Samek; Anja Veronica Witte (NeuroImage, 2022)

Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. - Simon Letzgus; Patrick Wagner 002; Jonas Lederer; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (IEEE Signal Process. Mag., 2022)

Overview of the Neural Network Compression and Representation (NNR) Standard. - Heiner Kirchhoffer; Paul Haase; Wojciech Samek; Karsten Müller 001; Hamed Rezazadegan Tavakoli; Francesco Cricri; Emre B. Aksu; Miska M. Hannuksela; Wei Jiang 001; Wei Wang 311; Shan Liu 001; Swayambhoo Jain; et al. (IEEE Trans. Circuits Syst. Video Technol., 2022)

CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding. - Felix Sattler; Arturo Marbán; Roman Rischke; Wojciech Samek (IEEE Trans. Netw. Sci. Eng., 2022)

XAI-based Comparison of Audio Event Classifiers with different Input Representations. - Annika Frommholz; Fabian Seipel; Sebastian Lapuschkin; Wojciech Samek; Johanna Vielhaben (CBMI, 2023)

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. - Alexander Binder; Leander Weber; Sebastian Lapuschkin; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CVPR, 2023)

Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. - Maximilian Dreyer; Reduan Achtibat; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CVPR Workshops, 2023)

Optimizing Explanations by Network Canonization and Hyperparameter Search. - Frederik Pahde; Galip Ümit Yolcu; Alexander Binder; Wojciech Samek; Sebastian Lapuschkin (CVPR Workshops, 2023)

Human-Centered Evaluation of XAI Methods. - Karam Dawoud; Wojciech Samek; Peter Eisert; Sebastian Lapuschkin; Sebastian Bosse (ICDM (Workshops), 2023)

Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. - Frederik Pahde; Maximilian Dreyer; Wojciech Samek; Sebastian Lapuschkin (MICCAI (2), 2023)

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. - Marco Aversa; Gabriel Nobis; Miriam Hägele; Kai Standvoss; Mihaela Chirica; Roderick Murray-Smith; Ahmed M. Alaa; Lukas Ruff; Daniela Ivanova; Wojciech Samek; Frederick Klauschen; Bruno Sanguinetti; et al. (NeurIPS, 2023)

XAI-based Comparison of Input Representations for Audio Event Classification. - Annika Frommholz; Fabian Seipel; Sebastian Lapuschkin; Wojciech Samek; Johanna Vielhaben (CoRR, 2023)

From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space. - Maximilian Dreyer; Frederik Pahde; Christopher J. Anders; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2023)

Layer-wise Feedback Propagation. - Leander Weber; Jim Berend; Alexander Binder; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2023)

Generative Fractional Diffusion Models. - Gabriel Nobis; Marco Aversa; Maximilian Springenberg; Michael Detzel; Stefano Ermon; Shinichi Nakajima; Roderick Murray-Smith; Sebastian Lapuschkin; Christoph Knochenhauer; Luis Oala; Wojciech Samek (CoRR, 2023)

DMLR: Data-centric Machine Learning Research - Past, Present and Future. - Luis Oala; Manil Maskey; Lilith Bat-Leah; Alicia Parrish; Nezihe Merve Gürel; Tzu-Sheng Kuo; Yang Liu 018; Rotem Dror; Danilo Brajovic; Xiaozhe Yao; Max Bartolo; William Gaviria Rojas; et al. (CoRR, 2023)

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond. - Anna Hedström; Leander Weber; Daniel Krakowczyk; Dilyara Bareeva; Franz Motzkus; Wojciech Samek; Sebastian Lapuschkin; Marina M.-C. Höhne (J. Mach. Learn. Res., 2023)

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus. - Anna Hedström; Philine Lou Bommer; Kristoffer Knutsen Wickstrøm; Wojciech Samek; Sebastian Lapuschkin; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

Data Models for Dataset Drift Controls in Machine Learning With Optical Images. - Luis Oala; Marco Aversa; Gabriel Nobis; Kurt Willis; Yoan Neuenschwander; Michèle Buck; Christian Matek; Jérôme Extermann; Enrico Pomarico; Wojciech Samek; Roderick Murray-Smith; Christoph Clausen; et al. (Trans. Mach. Learn. Res., 2023)

Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review. - Leon Witt; Mathis Heyer; Kentaroh Toyoda; Wojciech Samek; Dan Li 001 (IEEE Internet Things J., 2023)

Beyond explaining: Opportunities and challenges of XAI-based model improvement. - Leander Weber; Sebastian Lapuschkin; Alexander Binder; Wojciech Samek (Inf. Fusion, 2023)

Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. - Saúl Calderón Ramírez; Luis Oala; Jordina Torrents-Barrena; Shengxiang Yang; David A. Elizondo; Armaghan Moemeni; Simon Colreavy-Donnelly; Wojciech Samek; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IEEE Trans. Artif. Intell., 2023)

Data Models for Dataset Drift Controls in Machine Learning With Optical Images - Datasets. - Luis Oala; Marco Aversa; Gabriel Nobis; Kurt Willis; Yoan Neuenschwander; Michèle Buck; Christian Matek; Jérôme Extermann; Enrico Pomarico; Wojciech Samek; Roderick Murray-Smith; Christoph Clausen; et al. (Zenodo, 2023)

Evaluating deep transfer learning for whole-brain cognitive decoding. - Armin W. Thomas; Ulman Lindenberger; Wojciech Samek; Klaus-Robert Müller (J. Frankl. Inst., 2023)

From attribution maps to human-understandable explanations through Concept Relevance Propagation. - Reduan Achtibat; Maximilian Dreyer; Ilona Eisenbraun; Sebastian Bosse; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (Nat. Mac. Intell., 2023)

FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning. - Felix Sattler; Tim Korjakow; Roman Rischke; Wojciech Samek (IEEE Trans. Neural Networks Learn. Syst., 2023)

Langevin Cooling for Unsupervised Domain Translation. - Vignesh Srinivasan; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (IEEE Trans. Neural Networks Learn. Syst., 2023)

From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space. - Maximilian Dreyer; Frederik Pahde; Christopher J. Anders; Wojciech Samek; Sebastian Lapuschkin (AAAI, 2024)

Boosting Federated Learning with Diffusion Models for Non-IID and Imbalanced Data. - Maximilian Andreas Hoefler; Tatsiana Mazouka; Karsten Mueller; Wojciech Samek (IEEE Big Data, 2024)

Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression. - Dilyara Bareeva; Maximilian Dreyer; Frederik Pahde; Wojciech Samek; Sebastian Lapuschkin (CVPR Workshops, 2024)

Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations. - Maximilian Dreyer; Reduan Achtibat; Wojciech Samek; Sebastian Lapuschkin (CVPR Workshops, 2024)

Pruning by Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers. - Sayed Mohammad Vakilzadeh Hatefi; Maximilian Dreyer; Reduan Achtibat; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (ECCV Workshops (21), 2024)

XAI-Guided Insulator Anomaly Detection for Imbalanced Datasets. - Maximilian Andreas Hoefler; Karsten Müller 001; Wojciech Samek (ECCV Workshops (4), 2024)

Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization. - Rohan Reddy Mekala; Frederik Pahde; Simon Baur; Sneha Chandrashekar; Madeline Diep; Markus Wenzel 002; Eric L. Wisotzky; Galip Ümit Yolcu; Sebastian Lapuschkin; Jackie Ma; Peter Eisert; Mikael Lindvall; et al. (ECCV Workshops (20), 2024)

AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers. - Reduan Achtibat; Sayed Mohammad Vakilzadeh Hatefi; Maximilian Dreyer; Aakriti Jain; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek (ICML, 2024)

Position: Explain to Question not to Justify. - Przemyslaw Biecek; Wojciech Samek (ICML, 2024)

Active Learning with the nnUNet and Sample Selection with Uncertainty-Aware Submodular Mutual Information Measure. - Bernhard Föllmer; Kenrick Schulze; Christian Wald; Sebastian Stober; Wojciech Samek; Marc Dewey (MIDL, 2024)

Generative Fractional Diffusion Models. - 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; et al. (NeurIPS, 2024)

Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification. - Christian Tinauer; Anna Damulina; Maximilian Sackl; Martin Soellradl; Reduan Achtibat; Maximilian Dreyer; Frederik Pahde; Sebastian Lapuschkin; Reinhold Schmidt; Stefan Ropele; Wojciech Samek; Christian Langkammer (xAI (2), 2024)

Model Guidance via Explanations Turns Image Classifiers into Segmentation Models. - Xiaoyan Yu; Jannik Franzen; Wojciech Samek; Marina M.-C. Höhne; Dagmar Kainmueller (xAI (2), 2024)

PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits. - Maximilian Dreyer; Erblina Purelku; Johanna Vielhaben; Wojciech Samek; Sebastian Lapuschkin (XAI4CV, 2024)

DualView: Data Attribution from the Dual Perspective. - Galip Ümit Yolcu; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2024)

Explain to Question not to Justify. - Przemyslaw Biecek; Wojciech Samek (CoRR, 2024)

Blockchain and Artificial Intelligence: Synergies and Conflicts. - Leon Witt; Armando Teles Fortes; Kentaroh Toyoda; Wojciech Samek; Dan Li 001 (CoRR, 2024)

The Clever Hans Effect in Unsupervised Learning. - Jacob R. Kauffmann; Jonas Dippel; Lukas Ruff; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (CoRR, 2024)

PINNfluence: Influence Functions for Physics-Informed Neural Networks. - Jonas R. Naujoks; Aleksander Krasowski; Moritz Weckbecker; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek; René P. Klausen (CoRR, 2024)

Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond. - Dilyara Bareeva; Galip Ümit Yolcu; Anna Hedström; Niklas Schmolenski; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2024)

Spatial Shortcuts in Graph Neural Controlled Differential Equations. - Michael Detzel; Gabriel Nobis; Jackie Ma; Wojciech Samek (CoRR, 2024)

Optimizing Federated Learning by Entropy-Based Client Selection. - Andreas Lutz; Gabriele Steidl; Karsten Müller 001; Wojciech Samek (CoRR, 2024)

Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers. - Johanna Vielhaben; Dilyara Bareeva; Jim Berend; Wojciech Samek; Nils Strodthoff (CoRR, 2024)

Opportunities and limitations of explaining quantum machine learning. - Elies Gil-Fuster; Jonas R. Naujoks; Grégoire Montavon; Thomas Wiegand 001; Wojciech Samek; Jens Eisert (CoRR, 2024)

Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions. - Luca Longo; Mario Brcic; Federico Cabitza; Jaesik Choi; Roberto Confalonieri 001; Javier Del Ser; Riccardo Guidotti; Yoichi Hayashi; Francisco Herrera; Andreas Holzinger; Richard Jiang 001; Hassan Khosravi; et al. (Inf. Fusion, 2024)

AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark. - Sören Becker 001; Johanna Vielhaben; Marcel Ackermann 001; Klaus-Robert Müller; Sebastian Lapuschkin; Wojciech Samek (J. Frankl. Inst., 2024)

Explainable AI for time series via Virtual Inspection Layers. - Johanna Vielhaben; Sebastian Lapuschkin; Grégoire Montavon; Wojciech Samek (Pattern Recognit., 2024)

Neural Network Coding of Difference Updates for Efficient Distributed Learning Communication. - Daniel Becking; Karsten Müller 001; Paul Haase; Heiner Kirchhoffer; Gerhard Tech; Wojciech Samek; Heiko Schwarz; Detlev Marpe; Thomas Wiegand 001 (IEEE Trans. Multim., 2024)

Decentralized and Incentivized Federated Learning: A Blockchain-Enabled Framework Utilising Compressed Soft-Labels and Peer Consistency. - Leon Witt; Usama Zafar; KuoYeh Shen; Felix Sattler; Dan Li 001; Songtao Wang; Wojciech Samek (IEEE Trans. Serv. Comput., 2024)

From Clustering to Cluster Explanations via Neural Networks. - Jacob R. Kauffmann; Malte Esders; Lukas Ruff; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2024)

Explainable AI Reveals Clever Hans Effects in Unsupervised Learning Models: Code. - Jacob R. Kauffmann; Jonas Dippel; Lukas Ruff; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (Zenodo, 2024)

FADE: Why Bad Descriptions Happen to Good Features. - Bruno Puri; Aakriti Jain; Elena Golimblevskaia; Patrick Kahardipraja; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (ACL (Findings), 2025)

Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence. - Frederik Pahde; Maximilian Dreyer; Moritz Weckbecker; Leander Weber; Christopher J. Anders; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (ICLR, 2025)

Inspecting AI Like Engineers: From Explanation to Validation with SemanticLens. - Wojciech Samek (ICSOFT, 2025)

Explainable AI reveals Clever Hans effects in unsupervised learning models. - Jacob R. Kauffmann; Jonas Dippel; Lukas Ruff; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (Nat. Mac. Intell., 2025)

Explaining predictive uncertainty by exposing second-order effects. - Florian Bley; Sebastian Lapuschkin; Wojciech Samek; Grégoire Montavon (Pattern Recognit., 2025)

Evaluating Interpretable Methods via Geometric Alignment of Functional Distortions. - Anna Hedström; Philine Lou Bommer; Thomas F. Burns; Sebastian Lapuschkin; Wojciech Samek; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2025)

Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation. - Leander Weber; Jim Berend; Moritz Weckbecker; Alexander Binder; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (Trans. Mach. Learn. Res., 2025)

Mechanistic understanding and validation of large AI models with SemanticLens. - Maximilian Dreyer; Jim Berend; Tobias Labarta; Johanna Vielhaben; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek (CoRR, 2025)

Ensuring Medical AI Safety: Explainable AI-Driven Detection and Mitigation of Spurious Model Behavior and Associated Data. - Frederik Pahde; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek (CoRR, 2025)

Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs using PDEs. - Jost Arndt; Utku Isil; Michael Detzel; Wojciech Samek; Jackie Ma (CoRR, 2025)

ReReLRP - Remembering and Recognizing Tasks with LRP. - Karolina Bogacka; Maximilian Andreas Hoefler; Maria Ganzha; Wojciech Samek; Katarzyna Wasielewska-Michniewska (CoRR, 2025)

A Close Look at Decomposition-based XAI-Methods for Transformer Language Models. - Leila Arras; Bruno Puri; Patrick Kahardipraja; Sebastian Lapuschkin; Wojciech Samek (CoRR, 2025)

Post-Hoc Concept Disentanglement: From Correlated to Isolated Concept Representations. - Eren Erogullari; Sebastian Lapuschkin; Wojciech Samek; Frederik Pahde (CoRR, 2025)

ASIDE: Architectural Separation of Instructions and Data in Language Models. - Egor Zverev; Evgenii Kortukov; Alexander Panfilov; Soroush Tabesh; Alexandra Volkova; Sebastian Lapuschkin; Wojciech Samek; Christoph H. Lampert (CoRR, 2025)

Efficient Federated Learning Tiny Language Models for Mobile Network Feature Prediction. - Daniel Becking; Ingo Friese; Karsten Müller 001; Thomas Buchholz; Mandy Galkow-Schneider; Wojciech Samek; Detlev Marpe (CoRR, 2025)

Steering CLIP's vision transformer with sparse autoencoders. - Sonia Joseph; Praneet Suresh; Ethan Goldfarb; Lorenz Hufe; Yossi Gandelsman; Robert Graham; Danilo Bzdok; Wojciech Samek; Blake Aaron Richards (CoRR, 2025)

The Atlas of In-Context Learning: How Attention Heads Shape In-Context Retrieval Augmentation. - Patrick Kahardipraja; Reduan Achtibat; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2025)

From What to How: Attributing CLIP's Latent Components Reveals Unexpected Semantic Reliance. - Maximilian Dreyer; Lorenz Hufe; Jim Berend; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek (CoRR, 2025)

Relevance-driven Input Dropout: an Explanation-guided Regularization Technique. - Shreyas Gururaj; Lars Grüne; Wojciech Samek; Sebastian Lapuschkin; Leander Weber (CoRR, 2025)

Deep Learning-based Multi Project InP Wafer Simulation for Unsupervised Surface Defect Detection. - Emílio Dolgener Cantú; Rolf Klemens Wittmann; Oliver Abdeen; Patrick Wagner 002; Wojciech Samek; Moritz Baier; Sebastian Lapuschkin (CoRR, 2025)

Attribution-guided Pruning for Compression, Circuit Discovery, and Targeted Correction in LLMs. - Sayed Mohammad Vakilzadeh Hatefi; Maximilian Dreyer; Reduan Achtibat; Patrick Kahardipraja; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2025)

See What I Mean? CUE: A Cognitive Model of Understanding Explanations. - Tobias Labarta; Nhi Hoang; Katharina Weitz; Wojciech Samek; Sebastian Lapuschkin; Leander Weber (CoRR, 2025)

Leveraging Influence Functions for Resampling Data in Physics-Informed Neural Networks. - Jonas R. Naujoks; Aleksander Krasowski; Moritz Weckbecker; Galip Ümit Yolcu; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek; René P. Klausen (CoRR, 2025)

A Privacy Preserving System for Movie Recommendations Using Federated Learning. - David Neumann; Andreas Lutz; Karsten Müller 001; Wojciech Samek (Trans. Recomm. Syst., 2025)

Ensuring medical AI safety: interpretability-driven detection and mitigation of spurious model behavior and associated data. - Frederik Pahde; Thomas Wiegand 001; Sebastian Lapuschkin; Wojciech Samek (Mach. Learn., 2025)