3 papers
stat.ML2026
Extrapolation Guarantees for Perturbation Modeling Under the Additive Latent Shift Assumption
Julius von Kügelgen, Jakob Ketterer, Michael Vollenweider +4
We consider the problem of modeling the effects of perturbations like gene knockouts on measurements such as single-cell RNA counts. Given data for some perturbations, we aim to pr…
cs.LG2025
Fusion of Graph Neural Networks via Optimal Transport
Weronika Ormaniec, Michael Vollenweider, Elisa Hoskovec
In this paper, we explore the idea of combining GCNs into one model. To that end, we align the weights of different models layer-wise using optimal transport (OT). We present and e…
cs.LG2024
Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification
Michael Vollenweider, Manuel Schürch, Chiara Rohrer +3
Precision medicine has the potential to tailor treatment decisions to individual patients using machine learning (ML) and artificial intelligence (AI), but it faces significant cha…