arXiv:2608.29152v1 Announce Type: cross
Abstract: We study the empirical Sinkhorn estimator of the entropic optimal transport potentials under the uniform loss. Since the potentials are only unique u...
By Denis Belomestny
arXiv:2608. 13201v1 Announce Type: cross Abstract: We develop the statistical and algorithmic theory of inverse optimal transport (IOT) under the feature-parameterized cost C_theta(i,j) = -theta^T phi(i,j).
By Han Dong, Jiaming Li, Yongqiang Gong, Ruixi Li, Yin Liu
arXiv:2607. 15702v2 Announce Type: replace-cross Abstract: We develop a non-asymptotic approximation, sampling, and finite-iteration optimization theory for variational physics-informed approximation of uniformly monotone nonlinear multiscale elliptic equations.
By Ronald Katende
arXiv:2608. 28262v1 Announce Type: new Abstract: Entropic optimal transport (EOT) has been shown to offer a computationally tractable approximation to exact optimal transport.
By Ian Hsieh, Soumya Snigdha Kundu, Tom Vercauteren, Reuben Dorent
arXiv:2610. 35195v1 Announce Type: cross Abstract: We develop and analyze multilevel gradient-regularized Newton methods for unconstrained convex optimization with Lipschitz-continuous Hessians.
By Nick Tsipinakis, Matthias Voigt
arXiv:2606. 21828v2 Announce Type: replace-cross Abstract: Neural operators are increasingly used to warm-start Newton solvers for nonlinear PDEs, on the premise that a low test error places the initial guess inside the basin of attraction.
By Jaemin Oh, Youngkyu Lee, Jerome Darbon, George Em Karniadakis