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

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

5 September 2021

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

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Title
Homogenization with Guaranteed Bounds via Primal-Dual Physically Informed Neural Networks Liya Gaynutdinova M. Doškář O. Rokoš Ivana Pultarová PINN AI4CE 125 1 0 09 Sep 2025
Prediction error certification for PINNs: Theory, computation, and application to Stokes flow Birgit Hillebrecht B. Unger PINN 120 1 0 11 Aug 2025
The Finite Element Neural Network Method: One Dimensional Study Mohammed Abda Elsa Piollet Christopher Blake Frédérick P. Gosselin 363 0 0 21 Jan 2025
Computable Lipschitz Bounds for Deep Neural Networks Moreno Pintore Bruno Després 277 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 203 0 0 04 Oct 2024
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanicsComputer Methods in Applied Mechanics and Engineering (CMAME), 2023 Honghui Du QiZhi He AI4CE 365 12 0 21 Nov 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 271 1 0 27 Sep 2023
Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural NetworksAdvanced Modeling and Simulation in Engineering Sciences (AMSES), 2023 T. Şahin M. Danwitz A. Popp PINN 207 44 0 24 Aug 2023
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 492 167 0 22 Dec 2020