3 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
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…