Variational Physics Informed Neural Networks: the role of quadratures and test functions

5 September 2021

Papers citing "Variational Physics Informed Neural Networks: the role of quadratures and test functions"

8 / 8 papers shown

Title
The Finite Element Neural Network Method: One Dimensional Study Mohammed Abda Elsa Piollet Christopher Blake Frédérick P. Gosselin 71 0 0 21 Jan 2025
Computable Lipschitz Bounds for Deep Neural Networks Moreno Pintore Bruno Després 24 1 0 28 Oct 2024
HyResPINNs: Hybrid Residual Networks for Adaptive Neural and RBF Integration in Solving PDEs Madison Cooley Robert M. Kirby Shandian Zhe Varun Shankar PINN AI4CE 33 0 0 04 Oct 2024
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics Honghui Du QiZhi He AI4CE 60 5 0 21 Nov 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 43 0 0 27 Sep 2023
Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks T. Şahin M. Danwitz A. Popp PINN 34 20 0 24 Aug 2023
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 30 146 0 22 Dec 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 509 0 11 Mar 2020