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stat.ML2026
A Quantitative Approximation Framework for Flow Distillation in Diffusion Models
Weiguo Gao, Ming Li, Lei Shi +1
We develop a quantitative framework for diffusion distillation by viewing few step sampling as approximation through compositions of learned flow maps. For trajectory distillation…
cs.LG2026
ProFlow: Zero-Shot Physics-Consistent Sampling via Proximal Flow Guidance
Zichao Yu, Ming Li, Wenyi Zhang +2
Inferring physical fields from sparse observations while strictly satisfying partial differential equations (PDEs) is a fundamental challenge in computational physics. Recently, de…
cs.LG2026
Terminally constrained flow-based generative models from an optimal control perspective
Weiguo Gao, Ming Li, Qianxiao Li
We address the problem of sampling from terminally constrained distributions with pre-trained flow-based generative models through an optimal control formulation. Theoretically, we…