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2020 – today
- 2024
[b1]Moritz Böhle:
Towards designing inherently interpretable deep neural networks for image classification. Saarland University, Saarbrücken, Germany, 2024- [j3]Sukrut Rao
, Moritz Böhle, Bernt Schiele:
Better Understanding Differences in Attribution Methods via Systematic Evaluations. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4090-4101 (2024) - [j2]Moritz Böhle, Navdeeppal Singh, Mario Fritz, Bernt Schiele:
B-Cos Alignment for Inherently Interpretable CNNs and Vision Transformers. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4504-4518 (2024) - [c6]Sukrut Rao, Sweta Mahajan, Moritz Böhle, Bernt Schiele:
Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV (77) 2024: 444-461 - [i11]Amin Parchami-Araghi, Moritz Böhle, Sukrut Rao, Bernt Schiele:
Good Teachers Explain: Explanation-Enhanced Knowledge Distillation. CoRR abs/2402.03119 (2024) - [i10]Sukrut Rao, Sweta Mahajan, Moritz Böhle, Bernt Schiele:
Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. CoRR abs/2407.14499 (2024) - 2023
- [j1]Moritz Böhle, Mario Fritz, Bernt Schiele:
Optimising for Interpretability: Convolutional Dynamic Alignment Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7625-7638 (2023) - [c5]Sukrut Rao, Moritz Böhle, Amin Parchami-Araghi, Bernt Schiele:
Studying How to Efficiently and Effectively Guide Models with Explanations. ICCV 2023: 1922-1933 - [c4]Anna Kukleva, Moritz Böhle, Bernt Schiele, Hilde Kuehne, Christian Rupprecht:
Temperature Schedules for self-supervised contrastive methods on long-tail data. ICLR 2023 - [i9]Moritz Böhle, Mario Fritz, Bernt Schiele:
Holistically Explainable Vision Transformers. CoRR abs/2301.08669 (2023) - [i8]Sukrut Rao, Moritz Böhle, Bernt Schiele:
Better Understanding Differences in Attribution Methods via Systematic Evaluations. CoRR abs/2303.11884 (2023) - [i7]Sukrut Rao, Moritz Böhle, Amin Parchami-Araghi, Bernt Schiele:
Studying How to Efficiently and Effectively Guide Models with Explanations. CoRR abs/2303.11932 (2023) - [i6]Anna Kukleva, Moritz Böhle, Bernt Schiele, Hilde Kuehne, Christian Rupprecht:
Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data. CoRR abs/2303.13664 (2023) - [i5]Moritz Böhle, Navdeeppal Singh, Mario Fritz, Bernt Schiele:
B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers. CoRR abs/2306.10898 (2023) - 2022
- [c3]Sukrut Rao, Moritz Böhle, Bernt Schiele:
Towards Better Understanding Attribution Methods. CVPR 2022: 10213-10222 - [c2]Moritz Böhle, Mario Fritz, Bernt Schiele:
B-cos Networks: Alignment is All We Need for Interpretability. CVPR 2022: 10319-10328 - [i4]Moritz Böhle, Mario Fritz, Bernt Schiele:
B-cos Networks: Alignment is All We Need for Interpretability. CoRR abs/2205.10268 (2022) - [i3]Sukrut Rao, Moritz Böhle, Bernt Schiele:
Towards Better Understanding Attribution Methods. CoRR abs/2205.10435 (2022) - 2021
- [c1]Moritz Böhle, Mario Fritz, Bernt Schiele:
Convolutional Dynamic Alignment Networks for Interpretable Classifications. CVPR 2021: 10029-10038 - [i2]Moritz Böhle, Mario Fritz, Bernt Schiele:
Convolutional Dynamic Alignment Networks for Interpretable Classifications. CoRR abs/2104.00032 (2021) - [i1]Moritz Böhle, Mario Fritz, Bernt Schiele:
Optimising for Interpretability: Convolutional Dynamic Alignment Networks. CoRR abs/2109.13004 (2021)
Coauthor Index
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