Author

Anish Dhir

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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

Preprint Aug 2026

Foundation Models for Partial Causal Identification

This paper investigates the development of causal foundation models for bounding the effect of interventions and counterfactuals from observational data. We show that a canonical prior can be defined with full support over the space of structural causal models with discrete observables. With this canonical prior, we tr...

A. Bellot, Anish Dhir · 2 citations