3 papers
cs.LG2026
Rate-Optimal Noise Annealing in Semi-Dual Neural Optimal Transport: Tangential Identifiability, Off-Manifold Ambiguity, and Guaranteed Recovery
Raymond Chu, Jaewoong Choi, Dohyun Kwon
Semi-dual neural optimal transport learns a transport map via a max-min objective, yet training can converge to incorrect or degenerate maps. We fully characterize these spurious s…
math.AP2025
Guaranteeing Higher Order Convergence Rates for Accelerated Wasserstein Gradient Flow Schemes
Raymond Chu, Matt Jacobs
In this paper, we study higher-order-accurate-in-time minimizing movements schemes for Wasserstein gradient flows. We introduce a novel accelerated second-order scheme, leveraging…
math.AP2025
The supercooled Stefan problem: fractal freezing and the fine structure of maximal solutions
Raymond Chu, Inwon Kim, Sebastian Munoz
We study the supercooled Stefan problem in arbitrary dimensions. First, we study general solutions and their irregularities, showing generic fractal freezing and nucleation, based…