Klaus-Robert Müller
Klaus-Robert Müller
TU Berlin & Korea University & Google Brain & MPII
Verified email at tu-berlin.de
Title
Cited by
Cited by
Year
PRUNING AND/OR QUANTIZING MACHINE LEARNING PREDICTORS
W Samek, S Lapuschkin, S Wiedemann, P Seegerer, S Yeom, K Mueller, ...
US Patent App. 17/556,657, 2022
2022
Scrutinizing XAI using linear ground-truth data with suppressor variables
R Wilming, C Budding, KR Müller, S Haufe
Machine Learning, 1-21, 2022
2022
Künstliche Intelligenz als Lösung des PathologInnenmangels?
P Jurmeister, KR Müller, F Klauschen
Der Pathologe, 1-4, 2022
2022
Artificial intelligence: a solution for the lack of pathologists?
P Jurmeister, KR Müller, F Klauschen
Der Pathologe, 2022
2022
CONCEPTS FOR FEDERATED LEARNING, CLIENT CLASSIFICATION AND TRAINING DATA SIMILARITY MEASUREMENT
W Samek, F Sattler, T Wiegand, K Müller
US Patent App. 17/526,739, 2022
2022
Automatic Identification of Chemical Moieties
J Lederer, M Gastegger, KT Schütt, M Kampffmeyer, KR Müller, OT Unke
arXiv preprint arXiv:2203.16205, 2022
2022
Harmoni: a Method for Eliminating Spurious Interactions due to the Harmonic Components in Neuronal Data
MJ Idaji, J Zhang, T Stephani, G Nolte, KR Müller, A Villringer, VV Nikulin
NeuroImage 252 (15), 119053, 2022
12022
Deep Learning for Whole-Brain Cognitive Decoding
KR Müller, AW Thomas, W Samek
2022 10th International Winter Conference on Brain-Computer Interface (BCI), 1-3, 2022
2022
XAI for transformers: better explanations through conservative propagation
A Ali, T Schnake, O Eberle, G Montavon, KR Müller, L Wolf
arXiv preprint arXiv:2202.07304, 2022
12022
Super-resolution in Molecular Dynamics Trajectory Reconstruction with Bi-Directional Neural Networks
L Winkler, KR Müller, HE Sauceda
arXiv preprint arXiv:2201.01195, 2022
2022
Explaining the predictions of unsupervised learning models
G Montavon, J Kauffmann, W Samek, KR Müller
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2022
12022
xxAI-Beyond Explainable Artificial Intelligence
A Holzinger, R Goebel, R Fong, T Moon, KR Müller, W Samek
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2022
2022
Machine learning models predict the primary sites of head and neck squamous cell carcinoma metastases based on DNA methylation
M Leitheiser, D Capper, P Seegerer, A Lehmann, U Schüller, KR Müller, ...
The Journal of pathology 256 (4), 378-387, 2022
2022
Inverse design of 3d molecular structures with conditional generative neural networks
NWA Gebauer, M Gastegger, SSP Hessmann, KR Müller, KT Schütt
Nature Communications 13, 973, 2022
72022
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
132022
Towards robust explanations for deep neural networks
AK Dombrowski, CJ Anders, KR Müller, P Kessel
Pattern Recognition 121, 108194, 2022
102022
Langevin Cooling for Unsupervised Domain Translation
V Srinivasan, KR Müller, W Samek, S Nakajima
IEEE Transactions for Neural Networks and Learning Systems, doi: 10.1109 …, 2022
12022
Building and interpreting deep similarity models
O Eberle, J Büttner, F Kräutli, KR Müller, M Valleriani, G Montavon
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (3), 1149 …, 2022
172022
Toward Explainable AI for Regression Models
S Letzgus, P Wagner, J Lederer, W Samek, KR Müller, G Montavon
IEEE Signal Processing Magazine, arXiv preprint arXiv:2112.11407, 2021
2021
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging
A Hashemi, Y Gao, C Cai, S Ghosh, KR Müller, S Nagarajan, S Haufe
Advances in Neural Information Processing Systems 34, 2021
32021
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Articles 1–20