Separable PINN: Mitigating the Curse of Dimensionality in Physics-Informed Neural Networks

16 November 2022

Papers citing "Separable PINN: Mitigating the Curse of Dimensionality in Physics-Informed Neural Networks"

5 / 5 papers shown

Title
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 42 209 0 16 Jul 2021
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 91 126 0 14 Dec 2020
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 203 2,282 0 18 Oct 2020
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework C. Jiang S. Esmaeilzadeh Kamyar Azizzadenesheli K. Kashinath Mustafa A. Mustafa H. Tchelepi P. Marcus P. Prabhat Anima Anandkumar AI4CE 182 141 0 01 May 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 85 387 0 10 Mar 2020