Samek, Wojciech

46 publications

ICLRW 2025 ASIDE: Architectural Separation of Instructions and Data in Language Models Egor Zverev, Evgenii Kortukov, Alexander Panfilov, Soroush Tabesh, Sebastian Lapuschkin, Wojciech Samek, Christoph H. Lampert

NeurIPS 2025 Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers Johanna Vielhaben, Dilyara Bareeva, Jim Berend, Wojciech Samek, Nils Strodthoff

ICLRW 2025 Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers Johanna Vielhaben, Dilyara Bareeva, Jim Berend, Wojciech Samek, Nils Strodthoff

TMLR 2025 Efficient and Flexible Neural Network Training Through Layer-Wise Feedback Propagation Leander Weber, Jim Berend, Moritz Weckbecker, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

ICLRW 2025 Efficient and Flexible Neural Network Training Through Layer-Wise Feedback Propagation Leander Weber, Jim Berend, Moritz Weckbecker, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

MLJ 2025 Ensuring Medical AI Safety: Interpretability-Driven Detection and Mitigation of Spurious Model Behavior and Associated Data Frederik Pahde, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek

TMLR 2025 Evaluating Interpretable Methods via Geometric Alignment of Functional Distortions Anna Hedström, Philine Lou Bommer, Thomas F Burns, Sebastian Lapuschkin, Wojciech Samek, Marina MC Höhne

ICCV 2025 FedXDS: Leveraging Model Attribution Methods to Counteract Data Heterogeneity in Federated Learning Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek

ICLRW 2025 Fractional Brownian Bridges for Aligned Data Gabriel Nobis, Arina Belova, Maximilian Springenberg, Rembert Daems, Christoph Knochenhauer, Manfred Opper, Tolga Birdal, Wojciech Samek

NeurIPS 2025 Fractional Diffusion Bridge Models Gabriel Nobis, Maximilian Springenberg, Arina Belova, Rembert Daems, Christoph Knochenhauer, Manfred Opper, Tolga Birdal, Wojciech Samek

ICLR 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, Wojciech Samek, Sebastian Lapuschkin

TMLR 2025 Sparse, Efficient and Explainable Data Attribution with DualXDA Galip Ümit Yolcu, Moritz Weckbecker, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

DMLR 2025 Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs Using PDEs Jost Arndt, Utku Isil, Michael Detzel, Wojciech Samek, Jackie Ma

NeurIPS 2025 The Atlas of In-Context Learning: How Attention Heads Shape In-Context Retrieval Augmentation Patrick Kahardipraja, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

MIDL 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

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

DMLR 2024 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, 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 Karlaš, 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

AAAI 2024 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

NeurIPS 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, Luis Oala, Wojciech Samek

ICMLW 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, Luis Oala, Wojciech Samek

ICML 2024 Position: Explain to Question Not to Justify Przemyslaw Biecek, Wojciech Samek

ECCVW 2024 Pruning by Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

CVPRW 2024 Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin

NeurIPSW 2024 Spatial Shortcuts in Graph Neural Controlled Differential Equations Michael Detzel, Gabriel Nobis, Jackie Ma, Wojciech Samek

ECCVW 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, Eric L. Wisotzky, Galip Ümit Yolcu, Sebastian Lapuschkin, Jackie Ma, Peter Eisert, Mikael Lindvall, Adam A. Porter, Wojciech Samek

CVPRW 2024 Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-Based Explanations Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin

ECCVW 2024 XAI-Guided Insulator Anomaly Detection for Imbalanced Datasets Maximilian Andreas Hoefler, Karsten Müller, Wojciech Samek

TMLR 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, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti

ICMLW 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, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti

NeurIPS 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, Luis Oala

ICMLW 2023 NNCodec: An Open Source Software Implementation of the Neural Network Coding ISO/IEC Standard Daniel Becking, Paul Haase, Heiner Kirchhoffer, Karsten Müller, Wojciech Samek, Detlev Marpe

CVPRW 2023 Optimizing Explanations by Network Canonization and Hyperparameter Search Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin

MLOSS 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

CVPRW 2023 Revealing Hidden Context Bias in Segmentation and Object Detection Through Concept-Specific Explanations Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

CVPR 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

TMLR 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 MC Höhne

CVPRW 2022 Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek

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

CVPRW 2020 Dithered Backprop: A Sparse and Quantized Backpropagation Algorithm for More Efficient Deep Neural Network Training Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek

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

MLOSS 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

ICCVW 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

ICCVW 2017 Understanding and Comparing Deep Neural Networks for Age and Gender Classification Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller

CVPR 2016 Analyzing Classifiers: Fisher Vectors and Deep Neural Networks Sebastian Lapuschkin, Alexander Binder, Gregoire Montavon, Klaus-Robert Muller, Wojciech Samek

JMLR 2016 The LRP Toolbox for Artificial Neural Networks Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek

NeurIPS 2013 Robust Spatial Filtering with Beta Divergence Wojciech Samek, Duncan Blythe, Klaus-Robert Müller, Motoaki Kawanabe