4 papers · 1 filter
CausalSmith: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference
Jiyuan Tan, Vasilis Syrgkanis
Automating theoretical research requires generating candidate results and evaluating them reliably. Models keep getting better at the first, while the second remains hard. A common…
Adaptive Estimation and Inference in Conditional Moment Models via the Discrepancy Principle
Jiyuan Tan, Vasilis Syrgkanis
We study adaptive estimation and inference in ill-posed linear inverse problems defined by conditional moment restrictions. Existing regularized estimators such as Regularized Deep…
Mirror Descent on Riemannian Manifolds
Jiaxin Jiang, Lei Shi, Jiyuan Tan
Mirror Descent (MD) is a scalable first-order method widely used in large-scale optimization, with applications in image processing, policy optimization, and neural network trainin…
Estimation of Treatment Effects in Extreme and Unobserved Data
Jiyuan Tan, Jose Blanchet, Vasilis Syrgkanis
Causal effect estimation seeks to determine the impact of an intervention from observational data. However, the existing causal inference literature primarily addresses treatment e…