Data-driven discovery of Green's functions with human-understandable deep learning

1 May 2021

Papers citing "Data-driven discovery of Green's functions with human-understandable deep learning"

7 / 7 papers shown

Title
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains Yusuke Yamazaki Ali Harandi Mayu Muramatsu A. Viardin Markus Apel T. Brepols Stefanie Reese Shahed Rezaei AI4CE 39 12 0 21 May 2024
Approximation of Solution Operators for High-dimensional PDEs Nathan Gaby Xiaojing Ye 30 0 0 18 Jan 2024
Operator learning for hyperbolic partial differential equations Christopher Wang Alex Townsend 42 2 0 29 Dec 2023
Elliptic PDE learning is provably data-efficient N. Boullé Diana Halikias Alex Townsend 28 18 0 24 Feb 2023
Learning Green's functions associated with time-dependent partial differential equations N. Boullé Seick Kim Tianyi Shi Alex Townsend AI4CE 29 25 0 27 Apr 2022
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces George Stepaniants 49 15 0 26 Aug 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 247 2,298 0 18 Oct 2020