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Principled Acceleration of Iterative Numerical Methods Using Machine
  Learning

Principled Acceleration of Iterative Numerical Methods Using Machine Learning

17 June 2022
S. Arisaka
Qianxiao Li
ArXivPDFHTML

Papers citing "Principled Acceleration of Iterative Numerical Methods Using Machine Learning"

5 / 5 papers shown
Title
A Deep Conjugate Direction Method for Iteratively Solving Linear Systems
A Deep Conjugate Direction Method for Iteratively Solving Linear Systems
Ayano Kaneda
Osman Akar
Jingyu Chen
Victoria Kala
David Hyde
Joseph Teran
36
10
0
22 May 2022
Using neural networks to solve the 2D Poisson equation for electric
  field computation in plasma fluid simulations
Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations
Li Cheng
Ekhi Ajuria Illarramendi
Guillaume Bogopolsky
M. Bauerheim
B. Cuenot
45
19
0
27 Sep 2021
Meta-learning PINN loss functions
Meta-learning PINN loss functions
Apostolos F. Psaros
Kenji Kawaguchi
George Karniadakis
PINN
38
97
0
12 Jul 2021
Fourier Neural Operator for Parametric Partial Differential Equations
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
205
2,282
0
18 Oct 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
323
11,681
0
09 Mar 2017
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