Moritz Böhle

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers.

[BibT_eX]

[DOI]

CoRR, 2023

Using Explanations to Guide Models.

[BibT_eX]

[DOI]

CoRR, 2023

Better Understanding Differences in Attribution Methods via Systematic Evaluations.

[BibT_eX]

[DOI]

Sukrut Rao

CoRR, 2023

Holistically Explainable Vision Transformers.

[BibT_eX]

[DOI]

CoRR, 2023

Temperature Schedules for self-supervised contrastive methods on long-tail data.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Studying How to Efficiently and Effectively Guide Models with Explanations.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Towards Better Understanding Attribution Methods.

[BibT_eX]

[DOI]

Sukrut Rao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

B-cos Networks: Alignment is All We Need for Interpretability.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Convolutional Dynamic Alignment Networks for Interpretable Classifications.

[BibT_eX]

[DOI]