E-LIB Suche - Ergebnisse für: Böhle, Moritz

1

Towards designing inherently interpretable deep neural netw..:

Böhle, Moritz , 2024

2

Better Understanding Differences in Attribution Methods via..:

Rao, Sukrut ; Böhle, Moritz ; Schiele, Bernt
IEEE Transactions on Pattern Analysis and Machine Intelligence. 46 (2024) 6 - p. 4090-4101 , 2024

Link: https://doi.org/10.1109/..

3

B-Cos Alignment for Inherently Interpretable CNNs and Visio..:

Böhle, Moritz ; Singh, Navdeeppal ; Fritz, Mario.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 46 (2024) 6 - p. 4504-4518 , 2024

Link: https://doi.org/10.1109/..

4

Studying How to Efficiently and Effectively Guide Models wi..:

, In: 2023 IEEE/CVF International Conference on Computer Vision (ICCV),

Rao, Sukrut ; Bohle, Moritz ; Parchami-Araghi, Amin. - p. 1922-1933 , 2023

Link: https://doi.org/10.1109/..

5

Optimising for Interpretability: Convolutional Dynamic Alig..:

Böhle, Moritz ; Fritz, Mario ; Schiele, Bernt
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45 (2023) 6 - p. 7625-7638 , 2023

Link: https://doi.org/10.1109/..

6

Towards Better Understanding Attribution Methods:

, In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),

Rao, Sukrut ; Bohle, Moritz ; Schiele, Bernt - p. 10213-10222 , 2022

Link: https://doi.org/10.1109/..

7

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

, In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),

Bohle, Moritz ; Fritz, Mario ; Schiele, Bernt - p. 10319-10328 , 2022

Link: https://doi.org/10.1109/..

8

Layer-Wise Relevance Propagation for Explaining Deep Neural..:

Böhle, Moritz ; Eitel, Fabian ; Weygandt, Martin.
Frontiers in Aging Neuroscience. 11 (2019) - p. , 2019

Link: https://doi.org/10.3389/..

9

Temperature Schedules for Self-Supervised Contrastive Metho..:

Kukleva, Anna ; Böhle, Moritz ; Schiele, Bernt..
http://arxiv.org/abs/2303.13664. , 2023

Link: http://arxiv.org/abs/230..

10

Holistically Explainable Vision Transformers:

Böhle, Moritz ; Fritz, Mario ; Schiele, Bernt
http://arxiv.org/abs/2301.08669. , 2023

Link: http://arxiv.org/abs/230..

11

B-cos Alignment for Inherently Interpretable CNNs and Visio..:

Böhle, Moritz ; Singh, Navdeeppal ; Fritz, Mario.
http://arxiv.org/abs/2306.10898. , 2023

Link: http://arxiv.org/abs/230..

12

Using Explanations to Guide Models:

Rao, Sukrut ; Böhle, Moritz ; Parchami-Araghi, Amin.
http://arxiv.org/abs/2303.11932. , 2023

Link: http://arxiv.org/abs/230..

13

Better Understanding Differences in Attribution Methods via..:

Rao, Sukrut ; Böhle, Moritz ; Schiele, Bernt
http://arxiv.org/abs/2303.11884. , 2023

Link: http://arxiv.org/abs/230..

14

Towards Better Understanding Attribution Methods:

Rao, Sukrut ; Böhle, Moritz ; Schiele, Bernt
http://arxiv.org/abs/2205.10435. , 2022

Link: http://arxiv.org/abs/220..

15

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

Böhle, Moritz ; Fritz, Mario ; Schiele, Bernt
http://arxiv.org/abs/2205.10268. , 2022

Link: http://arxiv.org/abs/220..