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2020 – today
- 2024
[c7]Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz:
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. ICLR 2024- [c6]Kouroche Bouchiat, Alexander Immer, Hugo Yèche, Gunnar Rätsch, Vincent Fortuin:
Improving Neural Additive Models with Bayesian Principles. ICML 2024 - [i8]Hugo Yèche, Manuel Burger, Dinara Veshchezerova, Gunnar Rätsch:
Dynamic Survival Analysis for Early Event Prediction. CoRR abs/2403.12818 (2024) - 2023
- [c5]Hugo Yèche, Alizée Pace, Gunnar Rätsch, Rita Kuznetsova:
Temporal Label Smoothing for Early Event Prediction. ICML 2023: 39913-39938 - [c4]Rita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch:
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series. ML4H@NeurIPS 2023: 268-291 - [i7]Kouroche Bouchiat, Alexander Immer, Hugo Yèche, Gunnar Rätsch, Vincent Fortuin:
Laplace-Approximated Neural Additive Models: Improving Interpretability with Bayesian Inference. CoRR abs/2305.16905 (2023) - [i6]Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz:
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. CoRR abs/2306.01157 (2023) - [i5]Rita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch:
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series. CoRR abs/2311.08902 (2023) - 2022
- [i4]Hugo Yèche, Alizée Pace, Gunnar Rätsch, Rita Kuznetsova
:
Temporal Label Smoothing for Early Prediction of Adverse Events. CoRR abs/2208.13764 (2022) - [i3]Severin Husmann, Hugo Yèche, Gunnar Rätsch, Rita Kuznetsova:
On the Importance of Clinical Notes in Multi-modal Learning for EHR Data. CoRR abs/2212.03044 (2022) - 2021
- [c3]Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch:
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. ICML 2021: 11964-11974 - [c2]Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch:
HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data. NeurIPS Datasets and Benchmarks 2021 - [i2]Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch:
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. CoRR abs/2106.05142 (2021) - [i1]Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch:
HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data. CoRR abs/2111.08536 (2021)
2010 – 2019
- 2019
- [c1]Hugo Yèche, Justin Harrison, Tess Berthier:
UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics. iMIMIC/ML-CDS@MICCAI 2019: 12-20
Coauthor Index
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