Manuel Schürch

According to our database, Manuel Schürch authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification.

Michael Vollenweider, Manuel Schürch, Chiara Rohrer, Gabriele Gut, Michael Krauthammer, Andreas Wicki

CoRR, 2024

Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis.

Cécile Trottet, Manuel Schürch, Ahmed Allam, Imon Barua, Liubov Petelytska, Oliver Distler, Anna-Maria Hoffmann-Vold, Michael Krauthammer, EUSTAR collaborators

CoRR, 2024

Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes.

Xiaochen Zheng, Manuel Schürch, Xingyu Chen, Maria Angeliki Komninou, Reto Schüpbach, Ahmed Allam, Jan Bartussek, Michael Krauthammer

CoRR, 2024

Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data.

Manuel Schürch, Laura Boos, Viola Heinzelmann-Schwarz, Gabriele Gut, Michael Krauthammer, Andreas Wicki, Tumor Profiler Consortium

CoRR, 2024

Simple Contrastive Representation Learning for Time Series Forecasting.

Xiaochen Zheng, Xingyu Chen, Manuel Schürch, Amina Mollaysa, Ahmed Allam, Michael Krauthammer

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Correlated product of experts for sparse Gaussian process regression.

Manuel Schürch, Dario Azzimonti, Alessio Benavoli, Marco Zaffalon

Mach. Learn., May, 2023

Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent Processes.

Cécile Trottet, Manuel Schürch, Ahmed Allam, Imon Barua, Liubov Petelytska, Oliver Distler, Anna-Maria Hoffmann-Vold, Michael Krauthammer, EUSTAR collaborators

CoRR, 2023

Dynamic Local Attention with Hierarchical Patching for Irregular Clinical Time Series.

Xingyu Chen, Xiaochen Zheng, Amina Mollaysa, Manuel Schürch, Ahmed Allam, Michael Krauthammer

CoRR, 2023

Generating Personalized Insulin Treatments Strategies with Deep Conditional Generative Time Series Models.

Manuel Schürch, Xiang Li, Ahmed Allam, Giulia Rathmes, Amina Mollaysa, Claudia Cavelti-Weder, Michael Krauthammer

CoRR, 2023

SimTS: Rethinking Contrastive Representation Learning for Time Series Forecasting.

Xiaochen Zheng, Xingyu Chen, Manuel Schürch, Amina Mollaysa, Ahmed Allam, Michael Krauthammer

CoRR, 2023

2021

Sparse Information Filter for Fast Gaussian Process Regression.

Lucas Kania, Manuel Schürch, Dario Azzimonti, Alessio Benavoli

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

2020

Orthogonally Decoupled Variational Fourier Features.

Dario Azzimonti, Manuel Schürch, Alessio Benavoli, Marco Zaffalon

CoRR, 2020

Recursive estimation for sparse Gaussian process regression.

Manuel Schürch, Dario Azzimonti, Alessio Benavoli, Marco Zaffalon

Autom., 2020