ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2302.12888
  4. Cited By
Elliptic PDE learning is provably data-efficient
v1v2 (latest)

Elliptic PDE learning is provably data-efficient

Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2023
24 February 2023
N. Boullé
Diana Halikias
Alex Townsend
ArXiv (abs)PDFHTML

Papers citing "Elliptic PDE learning is provably data-efficient"

10 / 10 papers shown
Method of Manufactured Learning for Solver-free Training of Neural Operators
Method of Manufactured Learning for Solver-free Training of Neural Operators
Arth Sojitra
Omer San
AI4CE
194
0
0
17 Nov 2025
Query Efficient Structured Matrix Learning
Query Efficient Structured Matrix Learning
Noah Amsel
Pratyush Avi
Tyler Chen
Feyza Duman Keles
Chinmay Hegde
Cameron Musco
Christopher Musco
David Persson
107
0
0
25 Jul 2025
Learning where to learn: Training data distribution optimization for scientific machine learning
Learning where to learn: Training data distribution optimization for scientific machine learning
Nicolas Guerra
Nicholas H. Nelsen
Yunan Yang
OOD
310
0
0
27 May 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
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
485
7
0
02 Mar 2025
Orthogonal greedy algorithm for linear operator learning with shallow neural networkJournal of Computational Physics (JCP), 2025
Ye Lin
Jiwei Jia
Young Ju Lee
Ran Zhang
290
2
0
06 Jan 2025
Structure-Preserving Operator Learning
Structure-Preserving Operator Learning
Nacime Bouziani
Nicolas Boullé
198
3
0
01 Oct 2024
PETScML: Second-order solvers for training regression problems in
  Scientific Machine Learning
PETScML: Second-order solvers for training regression problems in Scientific Machine LearningPlatform for Advanced Scientific Computing Conference (PASC), 2024
Stefano Zampini
Umberto Zerbinati
George Turkyyiah
David E. Keyes
222
6
0
18 Mar 2024
Operator learning for hyperbolic partial differential equations
Operator learning for hyperbolic partial differential equations
Christopher Wang
Alex Townsend
363
6
0
29 Dec 2023
A Mathematical Guide to Operator Learning
A Mathematical Guide to Operator Learning
Nicolas Boullé
Alex Townsend
303
69
0
22 Dec 2023
One-shot learning for solution operators of partial differential
  equations
One-shot learning for solution operators of partial differential equationsNature Communications (Nat Commun), 2021
Priya Kasimbeg
Haiyang He
Rishikesh Ranade
Jay Pathak
Lu Lu
AI4CE
373
18
0
06 Apr 2021
1