One-shot learning for solution operators of partial differential equations

6 April 2021

Papers citing "One-shot learning for solution operators of partial differential equations"

8 / 8 papers shown

Title
A Bi-fidelity DeepONet Approach for Modeling Uncertain and Degrading Hysteretic Systems Subhayan De P. Brewick 31 0 0 25 Apr 2023
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration Zhongyi Jiang Min Zhu Dongzhuo Li Qiuzi Li Yanhua O. Yuan Lu Lu AI4CE 46 50 0 08 Mar 2023
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade C. Hill Lalit Ghule Jay Pathak AI4CE 33 7 0 11 Oct 2022
One-Shot Learning of Stochastic Differential Equations with Data Adapted Kernels Matthieu Darcy B. Hamzi Giulia Livieri H. Owhadi P. Tavallali 36 26 0 24 Sep 2022
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets Subhayan De Matthew J. Reynolds M. Hassanaly Ryan N. King Alireza Doostan AI4CE 26 37 0 03 Apr 2022
A composable autoencoder-based iterative algorithm for accelerating numerical simulations Rishikesh Ranade C. Hill Haiyang He Amir Maleki Norman Chang Jay Pathak AI4CE 41 5 0 07 Oct 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 50 494 0 09 Feb 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