Observed arrival · 2026-09-18
CausalSmith: an AI causal scientist with Lean-checked papers
CausalSmith presents econometric working papers whose formal statements, theorems, and lemmas are described as machine-verified in Lean 4.
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- Researchers in causal inference and formal methods
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- Listed papers link claims to Lean code, PDFs, slides, and an automated AI reviewer score.
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The homepage lists seven papers spanning treatment effects, network interference, optimal treatment values, transported complier effects, boundary regression, and instrumental-variable models. A featured result gives an explicit minimax mean-squared-error expression and describes a two-split hybrid estimator using empirical ratios and a Chebyshev reciprocal polynomial. Each paper exposes supporting artifacts such as Lean code, PDFs, slides, or online text.
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