| Recursive estimation for sparse Gaussian process regression M Schürch, D Azzimonti, A Benavoli, M Zaffalon Automatica 120, 109127, 2020 | 42 | 2020 |
| Simts: Rethinking contrastive representation learning for time series forecasting X Zheng, X Chen, M Schürch, A Mollaysa, A Allam, M Krauthammer arXiv preprint arXiv:2303.18205, 2023 | 36 | 2023 |
| Correlated product of experts for sparse Gaussian process regression M Schürch, D Azzimonti, A Benavoli, M Zaffalon Machine Learning 112 (5), 1411-1432, 2023 | 14 | 2023 |
| Generative time series models with interpretable latent processes for complex disease trajectories C Trottet, M Schürch, A Mollaysa, A Allam, M Krauthammer Deep Generative Models for Health Workshop NeurIPS 2023, 2023 | 8* | 2023 |
| pcalg: Methods for graphical models and causal inference M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ... R Package retrieved from https://CRAN. R-project. org/package= pcalg, 2021 | 8 | 2021 |
| Package ‘pcalg’ M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ... | 6 | 2024 |
| Generating Personalized Insulin Treatments Strategies with Conditional Generative Time Series Models M Schürch, X Li, A Allam, G Hofer, A Mollaysa, C Cavelti-Weder, ... Deep Generative Models for Health Workshop NeurIPS 2023, 2023 | 3* | 2023 |
| Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data M Schürch, L Boos, V Heinzelmann-Schwarz, G Gut, M Krauthammer, ... arXiv preprint arXiv:2402.12190, 2024 | 2 | 2024 |
| Sparse information filter for fast gaussian process regression L Kania, M Schürch, D Azzimonti, A Benavoli Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 2 | 2021 |
| Abstract B053: NucAE: Autoencoder-based enhancement of nucleosome occupancy signals from low-coverage cfDNA sequencing Z Balázs, J Radig, N Wolford, M Schürch, M Krauthammer Clinical Cancer Research 30 (21_Supplement), B053-B053, 2024 | | 2024 |
| Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification M Vollenweider, M Schürch, C Rohrer, G Gut, M Krauthammer, A Wicki arXiv preprint arXiv:2410.00509, 2024 | | 2024 |
| Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes X Zheng, M Schürch, X Chen, MA Komninou, R Schüpbach, A Allam, ... arXiv preprint arXiv:2405.03327, 2024 | | 2024 |
| Two-Stage Aggregation with Dynamic Local Attention for Irregular Time Series X Chen, X Zheng, A Mollaysa, M Schürch, A Allam, M Krauthammer arXiv preprint arXiv:2311.07744, 2023 | | 2023 |
| Dynamic Local Attention with Hierarchical Patching for Irregular Clinical Time Series. X Chen, X Zheng, A Mollaysa, M Schürch, A Allam, M Krauthammer CoRR, 2023 | | 2023 |
| Contributions to scalable gaussian processes MP Schürch | | 2022 |
| Orthogonally Decoupled Variational Fourier Features D Azzimonti, M Schürch, A Benavoli, M Zaffalon arXiv preprint arXiv:2007.06363, 2020 | | 2020 |
Dario AzzimontiIDSIAVerified email at idsia.ch
