UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs

9 August 2024

Papers citing "UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs"

8 / 8 papers shown

Title
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 470 2,384 0 18 Oct 2020
nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications G. Pang M. DÉlia M. Parks George Karniadakis PINN 48 154 0 08 Apr 2020
Learning Algebraic Multigrid Using Graph Neural Networks Ilay Luz Meirav Galun Haggai Maron Ronen Basri I. Yavneh 28 70 0 12 Mar 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 214 2,108 0 08 Oct 2019
Learning to Optimize Multigrid PDE Solvers D. Greenfeld Meirav Galun Ron Kimmel I. Yavneh Ronen Basri AI4CE 45 117 0 25 Feb 2019
Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss Rishi Sharma A. Farimani Joseph Gomes Peter K. Eastman Vijay S. Pande AI4CE 29 60 0 24 Jul 2018
Deep Learning the Physics of Transport Phenomena A. Farimani Joseph Gomes Vijay S. Pande AI4CE BDL 48 110 0 07 Sep 2017
Accelerating Eulerian Fluid Simulation With Convolutional Networks Jonathan Tompson Kristofer Schlachter Pablo Sprechmann Ken Perlin 80 534 0 13 Jul 2016