Physics-informed neural network simulation of multiphase poroelasticity
using stress-split sequential training

Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training

6 October 2021

Papers citing "Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training"

18 / 18 papers shown

Title
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 107 230 0 26 Apr 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 163 455 0 18 Dec 2020
Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture S. Niaki E. Haghighat Trevor Campbell Xinglong Li R. Vaziri AI4CE 100 208 0 27 Nov 2020
Energy-based error bound of physics-informed neural network solutions in elasticity Mengwu Guo E. Haghighat PINN 101 29 0 18 Oct 2020
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications N. Zobeiry K. D. Humfeld AI4CE 50 272 0 28 Sep 2020
Learning Unknown Physics of non-Newtonian Fluids B. Reyes Amanda A. Howard P. Perdikaris A. Tartakovsky PINN 30 48 0 26 Aug 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 121 906 0 28 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 69 224 0 09 Jul 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 120 2,543 0 17 Jun 2020
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao Sun Yang Liu PINN AI4CE 54 224 0 10 Jun 2020
A nonlocal physics-informed deep learning framework using the peridynamic differential operator E. Haghighat A. Bekar E. Madenci R. Juanes PINN 25 106 0 31 May 2020
Physics-informed deep learning for incompressible laminar flows Chengping Rao Hao Sun Yang Liu PINN AI4CE 98 223 0 24 Feb 2020
Physics-informed Neural Networks for Solving Nonlinear Diffusivity and Biot's equations T. Kadeethum T. Jørgensen H. Nick PINN AI4CE 82 110 0 19 Feb 2020
Physics Informed Deep Learning for Transport in Porous Media. Buckley Leverett Problem Cedric G. Fraces Adrien Papaioannou H. Tchelepi AI4CE PINN 54 19 0 15 Jan 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 89 293 0 13 Jan 2020
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 95 1,521 0 10 Jul 2019
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks Zhao Chen Vijay Badrinarayanan Chen-Yu Lee Andrew Rabinovich ODL 152 1,284 0 07 Nov 2017
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.6K 149,842 0 22 Dec 2014