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Stephan Wäldchen
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Unmasking Clever Hans predictors and assessing what machines really learn
S Lapuschkin, S Wäldchen, A Binder, G Montavon, W Samek, KR Müller
Nature communications 10 (1), 1096, 2019
11692019
The computational complexity of understanding binary classifier decisions
S Wäldchen, J Macdonald, S Hauch, G Kutyniok
Journal of Artificial Intelligence Research 70, 351–387-351–387, 2021
722021
A rate-distortion framework for explaining neural network decisions
J Macdonald, S Wäldchen, S Hauch, G Kutyniok
arXiv preprint arXiv:1905.11092, 2019
432019
Time-resolved response of cerebral stiffness to hypercapnia in humans
B Kreft, H Tzschätzsch, F Schrank, J Bergs, KJ Streitberger, S Wäldchen, ...
Ultrasound in medicine & biology 46 (4), 936-943, 2020
232020
Renormalizing entanglement distillation
S Waeldchen, J Gertis, ET Campbell, J Eisert
Physical Review Letters 116 (2), 020502, 2016
152016
Training characteristic functions with reinforcement learning: XAI-methods play connect four
S Wäldchen, S Pokutta, F Huber
International Conference on Machine Learning, 22457-22474, 2022
102022
Explaining neural network decisions is hard
J Macdonald, S Wäldchen, S Hauch, G Kutyniok
XXAI Workshop, 37th ICML, 2020
72020
Interpretability Guarantees with Merlin-Arthur Classifiers
S Wäldchen, K Sharma, B Turan, M Zimmer, S Pokutta
International Conference on Artificial Intelligence and Statistics, 1963-1971, 2024
6*2024
Towards Explainable Artificial Intelligence: Interpreting Neural Network Classifiers with Probabilistic Prime Implicants
S Wäldchen
PQDT-Global, 2022
52022
A Complete Characterisation of ReLU-Invariant Distributions
SW Jan Macdonald
Proceedings of The 25th International Conference on Artificial Intelligence …, 2022
32022
Hardness of Deceptive Certificate Selection
S Wäldchen
World Conference on Explainable Artificial Intelligence, 415-427, 2023
12023
A Rate-Distortion Framework for Explaining Deep Neural Network Decisions
S Waeldchen, J Macdonald, S Hauch, G Kutyniok
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