Author

Yu-Che Gao

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#machine learning Preprint Sep 2026

CIDER-FM: Foundation Models for Causal Inference from Diverse Experimental Regimes

Causal foundation models (CFMs) amortise causal inference over priors of synthetic structural causal models (SCMs), predicting the effect of an experiment on a specific variable. However, observational data alone may leave multiple causal models compatible with available evidence, while experimental data with intervent...

Yu-Che Gao, Arik Reuter, Si-Yuan Guo et al. · 0 citations

Jul 2026

PerturbPFN: Probing the Limits of Synthetic Priors in Drug Perturbation Modelling

The results show that PerturbPFN offers a complementary trade-off to specialized baselines, achieving competitive perturbation prediction with low inference cost while exposing interpretable intermediate estimates of targets, strengths, and system structure.

Yu-Che Gao, José Miguel Hernández-Lobato, Siyuan Guo · arXiv.org · 2 citations