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2020 – today
- 2024
[c8]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. AAAI 2024: 21046-21054- [c7]Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin:
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations. CVPR Workshops 2024: 3491-3501 - [c6]Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin:
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression. CVPR Workshops 2024: 3532-3541 - [c5]Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek:
AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers. ICML 2024 - [c4]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. xAI (2) 2024: 202-216 - [i11]Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek:
AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers. CoRR abs/2402.05602 (2024) - [i10]Maximilian Dreyer, Erblina Purelku, Johanna Vielhaben, Wojciech Samek, Sebastian Lapuschkin:
PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits. CoRR abs/2404.06453 (2024) - [i9]Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin:
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression. CoRR abs/2404.09601 (2024) - [i8]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. CoRR abs/2404.10433 (2024) - [i7]Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers. CoRR abs/2408.12568 (2024) - 2023
- [j1]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. Nat. Mac. Intell. 5(9): 1006-1019 (2023) - [c3]Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. CVPR Workshops 2023: 3829-3839 - [c2]Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin:
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. MICCAI (2) 2023: 596-606 - [i6]Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin:
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. CoRR abs/2303.12641 (2023) - [i5]Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin:
From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space. CoRR abs/2308.09437 (2023) - [i4]Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin:
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations. CoRR abs/2311.16681 (2023) - 2022
- [i3]Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
From "Where" to "What": Towards Human-Understandable Explanations through Concept Relevance Propagation. CoRR abs/2206.03208 (2022) - [i2]Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. CoRR abs/2211.11426 (2022) - 2021
- [i1]Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin:
ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. CoRR abs/2109.04236 (2021) - 2020
- [c1]Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin:
ECQ x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. xxAI@ICML 2020: 271-296
Coauthor Index
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