Meta-learning Pseudo-differential Operators with Deep Neural Networks

16 June 2019

Papers citing "Meta-learning Pseudo-differential Operators with Deep Neural Networks"

9 / 9 papers shown

Title
Operator learning for hyperbolic partial differential equations Christopher Wang Alex Townsend 34 2 0 29 Dec 2023
Inverse Problems with Learned Forward Operators Simon Arridge Andreas Hauptmann Yury Korolev 28 1 0 21 Nov 2023
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 20 11 0 28 Sep 2022
Learning Green's functions associated with time-dependent partial differential equations N. Boullé Seick Kim Tianyi Shi Alex Townsend AI4CE 21 25 0 27 Apr 2022
Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer B. Keith U. Khristenko B. Wohlmuth 17 7 0 23 Jul 2021
How many moments does MMD compare? Rustem Takhanov 14 0 0 27 Jun 2021
Learning the geometry of wave-based imaging K. Kothari Maarten V. de Hoop Ivan Dokmanić AI4CE 16 8 0 10 Jun 2020
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks Yingzhou Li Xiuyuan Cheng Jianfeng Lu 21 23 0 18 May 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 317 11,681 0 09 Mar 2017