| Neighborhood contrastive learning applied to online patient monitoring H Yèche, G Dresdner, F Locatello, M Hüser, G Rätsch International Conference on Machine Learning (ICML), 11964-11974, 2021 | 32 | 2021 |
| UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics H Yeche, J Harrison, T Berthier Interpretability of Machine Intelligence in Medical Image Computing and …, 2019 | 28 | 2019 |
| HiRID-ICU-Benchmark--A Comprehensive Machine Learning Benchmark on High-resolution ICU Data H Yèche, R Kuznetsova, M Zimmermann, M Hüser, X Lyu, M Faltys, ... NeurIPS 2021 Datasets and Benchmarks, 2021 | 22 | 2021 |
| On the Importance of Clinical Notes in Multi-modal Learning for EHR Data S Husmann, H Yèche, G Rätsch, R Kuznetsova Workshop on Learning from Time Series for Health, 36th Conference on Neural …, 2022 | 6 | 2022 |
| A comprehensive ml-based respiratory monitoring system for physiological monitoring & resource planning in the icu M Hüser, X Lyu, M Faltys, A Pace, M Hoche, SL Hyland, H Yèche, ... medRxiv, 2024.01. 23.24301516, 2024 | 4 | 2024 |
| Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding A Pace, H Yèche, B Schölkopf, G Rätsch, G Tennenholtz International Conference on Learning Representations (ICLR), 2023 | 2 | 2023 |
| Laplace-Approximated Neural Additive Models: Improving Interpretability with Bayesian Inference K Bouchiat, A Immer, H Yèche, G Rätsch, V Fortuin arXiv preprint arXiv:2305.16905, 2023 | 2 | 2023 |
| On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series R Kuznetsova, A Pace, M Burger, H Yèche, G Rätsch Machine Learning for Health (ML4H), 268-291, 2023 | 1 | 2023 |
| Dynamic Survival Analysis for Early Event Prediction H Yèche, M Burger, D Veshchezerova, G Rätsch CHIL 2024, 2024 | | 2024 |
| Linearized Laplace Inference in Neural Additive Models K Bouchiat, A Immer, H Yèche, V Fortuin Fifth Symposium on Advances in Approximate Bayesian Inference, 2023 | | 2023 |
| Improving Neural Additive Models with Bayesian Principles K Bouchiat, A Immer, H Yèche, G Rätsch, V Fortuin | | 2023 |
| Temporal Label Smoothing for Early Events Prediction H Yèche, A Pace, G Rätsch, R Kuznetsova 40th International Conference on Machine Learning (ICML), PMLR 202:39913 …, 2022 | | 2022 |
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
