Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces

26 August 2021

Papers citing "Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces"

6 / 6 papers shown

Title
Error Bounds for Learning with Vector-Valued Random Features S. Lanthaler Nicholas H. Nelsen 27 12 0 26 May 2023
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 23 11 0 28 Sep 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu Jose H. Blanchet Lexing Ying 35 7 0 15 May 2022
Learning particle swarming models from data with Gaussian processes Jinchao Feng Charles Kulick Yunxiang Ren Sui Tang 26 5 0 04 Jun 2021
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 208 2,287 0 18 Oct 2020
A reproducing kernel Hilbert space approach to functional linear regression M. Yuan Tommaso Cai 95 277 0 12 Nov 2012