4 papers
A Theory on Flow Matching with Neural Networks
Yihan He, Qishuo Yin, Yuan Cao +2
In this work, we develop theoretical foundation for flow matching with neural-network-parameterized conditional velocity fields. We establish convergence guarantees for gradient de…
Goedel-Architect: Streamlining Formal Theorem Proving with Blueprint Generation and Refinement
Jui-Hui Chung, Ziyang Cai, Zihao Li +14
We introduce Goedel-Architect, an agentic framework for formal theorem proving in Lean 4 centered on blueprint generation and refinement. A blueprint is a dependency graph of defin…
Optimally taming biases in black-box models for efficient semiparametric estimation
Yihong Gu, Qishuo Yin, Tianxi Cai +1
Modern semiparametric estimation often relies on flexible black-box machine learning methods to estimate nuisance functions, raising a fundamental question: how do nuisance estimat…
Factor Informed Double Deep Learning For Average Treatment Effect Estimation
Jianqing Fan, Soham Jana, Sanjeev Kulkarni +1
We investigate the problem of estimating the average treatment effect (ATE) under a very general setup where the covariates can be high-dimensional, highly correlated, and can have…