Minimax Optimal Kernel Operator Learning via Multilevel Training

Minimax Optimal Kernel Operator Learning via Multilevel Training

28 September 2022

Jose H. Blanchet

Papers citing "Minimax Optimal Kernel Operator Learning via Multilevel Training"

12 / 12 papers shown

Title
Operator Learning Using Random Features: A Tool for Scientific Computing Nicholas H. Nelsen Andrew M. Stuart 39 12 0 12 Aug 2024
Optimal Estimation of Structured Covariance Operators Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 31 3 0 04 Aug 2024
Base Models for Parabolic Partial Differential Equations Xingzi Xu Ali Hasan Jie Ding Vahid Tarokh 35 1 0 17 Jul 2024
Operator Learning: Algorithms and Analysis Nikola B. Kovachki S. Lanthaler Andrew M. Stuart 40 22 0 24 Feb 2024
Spectrally Transformed Kernel Regression Runtian Zhai Rattana Pukdee Roger Jin Maria-Florina Balcan Pradeep Ravikumar BDL 21 2 0 01 Feb 2024
A Mathematical Guide to Operator Learning Nicolas Boullé Alex Townsend 31 36 0 22 Dec 2023
Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 21 4 0 25 Oct 2023
Error Bounds for Learning with Vector-Valued Random Features S. Lanthaler Nicholas H. Nelsen 27 12 0 26 May 2023
Domain Generalization by Functional Regression Markus Holzleitner S. Pereverzyev Werner Zellinger OOD 21 4 0 09 Feb 2023
Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem Mattes Mollenhauer Nicole Mücke T. Sullivan 22 24 0 16 Nov 2022
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 205 2,282 0 18 Oct 2020
A note on estimation in Hilbertian linear models Siegfried Hormann Łukasz Kidziński 68 34 0 14 Aug 2012