Wiegand, Thomas

9 publications

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

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

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

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

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