Differentially private federated learning: A client level perspective RC Geyer, T Klein, M Nabi arXiv preprint arXiv:1712.07557, 2017 | 1712 | 2017 |
Differentially private federated learning: A client level perspective. arXiv 2017 RC Geyer, T Klein, M Nabi arXiv preprint arXiv:1712.07557, 0 | 41 | |
Transfer learning by adaptive merging of multiple models R Geyer, L Corinzia, V Wegmayr International Conference on Medical Imaging with Deep Learning, 185-196, 2019 | 14 | 2019 |
Invariant anomaly detection under distribution shifts: a causal perspective J Carvalho, M Zhang, R Geyer, C Cotrini, JM Buhmann Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
Building an interdisciplinary program of cardiovascular research at the Swiss Federal Institute of Technology–the ETHeart story AP Kourouklis, X Wu, RC Geyer, V Exarchos, T Nazari, J Kaemmel, ... Iscience 25 (10), 2022 | 2 | 2022 |
Measuring Orthogonality in Representations of Generative Models RC Geyer, A Torcinovich, JB Carvalho, A Meyer, JM Buhmann arXiv preprint arXiv:2407.03728, 2024 | | 2024 |
Ambient Intelligence in Postoperative Critical Care: First Observations of a Novel Monitoring Approach A Meyer, R Geyer, P Lanmüller, F Laumer, A Beuret, B Pfahringer, ... The Thoracic and Cardiovascular Surgeon 70 (S 01), DGTHG-V112, 2022 | | 2022 |
Beyond Disentanglement: On the Orthogonality of Learned Representations RC Geyer, A Torcinovich, JBS Carvalho, A Meyer, JM Buhmann | | |