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Christopher J. Anders
Christopher J. Anders
Machine Learning Group, Technische Universität Berlin
Bestätigte E-Mail-Adresse bei tu-berlin.de
Titel
Zitiert von
Zitiert von
Jahr
Explaining deep neural networks and beyond: A review of methods and applications
W Samek, G Montavon, S Lapuschkin, CJ Anders, KR Müller
Proceedings of the IEEE 109 (3), 247-278, 2021
1622021
Explanations can be manipulated and geometry is to blame
AK Dombrowski, M Alber, C Anders, M Ackermann, KR Müller, P Kessel
Advances in Neural Information Processing Systems 32, 2019
1442019
Toward interpretable machine learning: Transparent deep neural networks and beyond
W Samek, G Montavon, S Lapuschkin, CJ Anders, KR Müller
822020
Estimation of thermodynamic observables in lattice field theories with deep generative models
KA Nicoli, CJ Anders, L Funcke, T Hartung, K Jansen, P Kessel, ...
Physical review letters 126 (3), 032001, 2021
362021
Fairwashing explanations with off-manifold detergent
CJ Anders, P Pasliev, AK Dombrowski, KR Müller, P Kessel
Thirty-seventh International Conference on Machine Learning, 2020
342020
Understanding patch-based learning of video data by explaining predictions
CJ Anders, G Montavon, W Samek, KR Müller
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 297-309, 2019
23*2019
Finding and removing Clever Hans: Using explanation methods to debug and improve deep models
CJ Anders, L Weber, D Neumann, W Samek, KR Müller, S Lapuschkin
Information Fusion 77, 261-295, 2022
152022
Towards robust explanations for deep neural networks
AK Dombrowski, CJ Anders, KR Müller, P Kessel
Pattern Recognition 121, 108194, 2022
122022
Software for Dataset-wide XAI: From local explanations to global insights with Zennit, CoRelAy, and ViRelAy
CJ Anders, D Neumann, W Samek, KR Müller, S Lapuschkin
arXiv preprint arXiv:2106.13200, 2021
112021
Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans' ed
CJ Anders, T Marinč, D Neumann, W Samek, KR Müller, S Lapuschkin
112019
Toward interpretable machine learning: Transparent deep neural networks and beyond. arXiv 2020
W Samek, G Montavon, S Lapuschkin, CJ Anders, KR Müller
arXiv preprint arXiv:2003.07631, 2003
82003
Toward interpretable machine learning: Transparent deep neural networks and beyond. arXiv
W Samek, G Montavon, S Lapuschkin, CJ Anders, KR Müller
52020
PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging
F Pahde, L Weber, CJ Anders, W Samek, S Lapuschkin
arXiv preprint arXiv:2202.03482, 2022
12022
Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse
KA Nicoli, C Anders, L Funcke, T Hartung, K Jansen, P Kessel, ...
arXiv preprint arXiv:2111.11303, 2021
2021
Explanations can be manipulated and geometry is to blame Open Website
AK Dombrowski, M Alber, CJ Anders, M Ackermann, KR Muller, P Kessel
Towards robust explanations for deep neural networks Open Website
AK Dombrowski, CJ Anders, KR Muller, P Kessel
REGULAR PAPERS ISSUE
C She, C Sun, Z Gu, Y Li, C Yang, HV Poor, B Vucetic, W Samek, ...
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