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Vasilis Syrgkanis

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Review 2026

CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference

CausalForge is presented, a framework for automated theoretical research in causal inference grounded in the Lean proof assistant, which combines Causalean, a foundational Lean library for causal inference, with CausalSmith, a self-improving agentic pipeline that selects research topics, proposes results, formalizes st...

Ji-Yuan Tan, Vasilis Syrgkanis · 0 citations
#machine learning Preprint Oct 2022

Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects

We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multiple treatments sequentially, according to an adaptive policy that depends on a latent, endogenously time-varying confounding state. Under a low-rank latent factor model assumption...

Anish Agarwal, Sukjin Han, Dwaipayan Saha et al. · 3 citations
#machine learning Review Jul 2026

CausalSmith: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference

A framework for automated theoretical research in causal inference built on the Lean proof assistant, where a proof is checked by a program rather than read by a referee is presented, where a proof is checked by a program rather than read by a referee.

Jiyuan Tan, Vasilis Syrgkanis · 0 citations

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