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2305.04962
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Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs
8 May 2023
Pau Batlle
Yifan Chen
Bamdad Hosseini
H. Owhadi
Andrew M. Stuart
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Papers citing
"Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs"
15 / 15 papers shown
Title
Solving Nonlinear PDEs with Sparse Radial Basis Function Networks
Zihan Shao
Konstantin Pieper
Xiaochuan Tian
24
0
0
12 May 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
Yasamin Jalalian
Juan Felipe Osorio Ramirez
Alexander W. Hsu
Bamdad Hosseini
H. Owhadi
39
0
0
02 Mar 2025
Reduced Order Models and Conditional Expectation -- Analysing Parametric Low-Order Approximations
Hermann G. Matthies
42
0
0
17 Feb 2025
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
Jonghyeon Lee
B. Hamzi
Boya Hou
H. Owhadi
G. Santin
Umesh Vaidya
70
1
0
21 Dec 2024
Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
Zhitong Xu
Da Long
Yiming Xu
Guang Yang
Shandian Zhe
Houman Owhadi
30
0
0
15 Oct 2024
Physics-informed kernel learning
Nathan Doumèche
Francis Bach
Gérard Biau
Claire Boyer
PINN
29
2
0
20 Sep 2024
Gaussian process learning of nonlinear dynamics
Dongwei Ye
Mengwu Guo
16
4
0
19 Dec 2023
Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots
Théo Bourdais
Pau Batlle
Xianjin Yang
Ricardo Baptista
Nicolas Rouquette
H. Owhadi
16
0
0
28 Nov 2023
Coupling parameter and particle dynamics for adaptive sampling in Neural Galerkin schemes
Yuxiao Wen
Eric Vanden-Eijnden
Benjamin Peherstorfer
13
12
0
27 Jun 2023
Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes
Yifan Chen
H. Owhadi
F. Schafer
26
30
0
03 Apr 2023
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach
Yongcun Song
Xiaoming Yuan
Hangrui Yue
PINN
22
6
0
16 Feb 2023
A Kernel Approach for PDE Discovery and Operator Learning
D. Long
Nicole Mrvaljević
Shandian Zhe
Bamdad Hosseini
16
7
0
14 Oct 2022
One-Shot Learning of Stochastic Differential Equations with Data Adapted Kernels
Matthieu Darcy
B. Hamzi
Giulia Livieri
H. Owhadi
P. Tavallali
23
25
0
24 Sep 2022
Bayesian Numerical Methods for Nonlinear Partial Differential Equations
Junyang Wang
Jon Cockayne
O. Chkrebtii
T. Sullivan
Chris J. Oates
38
19
0
22 Apr 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
203
2,281
0
18 Oct 2020
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