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cs.LG2026
Learn Feasibility Once, Optimize All Objectives: Derivative-Free Diffusion Models for Chance-Constrained Programming
Ziwen Liu, Yan Liu, Congying Han +3
Chance-constrained programs (CCPs) optimize decisions under uncertainty by limiting the probability of constraint violation. Despite advances in traditional and learning-based appr…
cs.CV2026
Resolving Endpoint Underfitting in Diffusion Bridges via Noise Alignment
Yurong Gao, Zicheng Zhang, Congying Han +2
Diffusion bridge models offer a powerful framework for connecting two data distributions, such as in image restoration and translation. Many existing methods learn this bridge by m…