Optimal Transport-Inspired Deep Learning Framework for Slow-Decaying Kolmogorov \({n}\)-Width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel - researchr publication

researchr

You are not signed in
Sign in
Sign up

Moaad Khamlich, Federico Pichi, Gianluigi Rozza. Optimal Transport-Inspired Deep Learning Framework for Slow-Decaying Kolmogorov \({n}\)-Width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel. SIAM J. Scientific Computing, 47(2):235, 2025. [doi]

Abstract is missing.

runs on WebDSL