Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics

21 November 2023

Papers citing "Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics"

6 / 6 papers shown

Title
Deep autoencoders for physics-constrained data-driven nonlinear materials modeling Xiaolong He Qizhi He Jiun-Shyan Chen AI4CE PINN SyDa 29 56 0 03 Sep 2022
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sifan Wang Hanwen Wang P. Perdikaris 131 438 0 18 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 2,281 0 18 Oct 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 508 0 11 Mar 2020
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications E. Samaniego C. Anitescu S. Goswami Vien Minh Nguyen-Thanh Hongwei Guo Khader M. Hamdia Timon Rabczuk X. Zhuang PINN AI4CE 145 1,338 0 27 Aug 2019