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

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]

This author has not been identified. Look up 'Moaad Khamlich' in GoogleThis author has not been identified. Look up 'Federico Pichi' in GoogleThis author has not been identified. Look up 'Gianluigi Rozza' in Google

runs on WebDSL