collaborators

8 papers

cs.LG2026

Support Selection Beyond Smooth DAG Exactness: Completion Geometry,Score Margins, and Selective Certificates

Rui Wu, Zongyuan Chen, Hong Xie

Smooth acyclicity constraints answer whether a weighted support is a DAG, whereas structure learning asks which support change should be made. Existing analyses establish degenerac…

cs.LG2026

Projective Graph Residualization: Variation-Allocation Frontiers for Control-Function IV

Rui Wu, Zongyuan Chen, Hong Xie +2

Control-function instrumental-variable estimators pass an estimated first-stage residual to an outcome model. The residual must retain the latent control direction while leaving en…

cs.LG2026

Optimization-Free Topological Sort for Causal Discovery via the Schur Complement of Score Jacobians

Rui Wu, Hong Xie

Continuous causal discovery typically couples representation learning with structural optimization via non-convex acyclicity penalties, which subjects solvers to local optima and r…

cs.LG2026

The Causal Uncertainty Principle: Manifold Tearing and the Topological Limits of Counterfactual Interventions

Rui Wu, Hong Xie, Yongjun Li

Judea Pearl's do-calculus provides a foundation for causal inference, but its translation to continuous generative models remains fraught with geometric challenges. We establish th…

cs.LG2026

Cohomological Obstructions to Global Counterfactuals: A Sheaf-Theoretic Foundation for Generative Causal Models

Rui Wu, Hong Xie, Yongjun Li

Current continuous generative models (e.g., Diffusion Models, Flow Matching) implicitly assume that locally consistent causal mechanisms naturally yield globally coherent counterfa…

cs.LG2026

Causal Schrödinger Bridges: Constrained Optimal Transport on Structural Manifolds

Rui Wu, Li YongJun

Generative modeling typically seeks the path of least action via deterministic flows (ODE). While effective for in-distribution tasks, we argue that these deterministic paths becom…