Enhanced Physics-Informed Neural Networks with Augmented Lagrangian
Relaxation Method (AL-PINNs)

Enhanced Physics-Informed Neural Networks with Augmented Lagrangian Relaxation Method (AL-PINNs)

29 April 2022

Papers citing "Enhanced Physics-Informed Neural Networks with Augmented Lagrangian Relaxation Method (AL-PINNs)"

17 / 17 papers shown

Title
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks Youngsik Hwang Dong-Young Lim AI4CE 86 3 0 27 Sep 2024
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 56 79 0 20 Sep 2021
Lagrangian dual framework for conservative neural network solutions of kinetic equations H. Hwang Hwijae Son 35 7 0 23 Jun 2021
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions Ameya Dilip Jagtap Yeonjong Shin Kenji Kawaguchi George Karniadakis ODL 72 134 0 20 May 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 95 516 0 09 Feb 2021
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation Jungeun Kim Kookjin Lee Dongeun Lee Sheo Yon Jin Noseong Park PINN AI4CE 50 81 0 04 Dec 2020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 72 458 0 07 Sep 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 130 909 0 28 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 72 224 0 09 Jul 2020
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains Matthew Tancik Pratul P. Srinivasan B. Mildenhall Sara Fridovich-Keil N. Raghavan Utkarsh Singhal R. Ramamoorthi Jonathan T. Barron Ren Ng 116 2,418 0 18 Jun 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 131 2,548 0 17 Jun 2020
Lagrangian Duality for Constrained Deep Learning Ferdinando Fioretto Pascal Van Hentenryck Terrence W.K. Mak Cuong Tran Federico Baldo M. Lombardi PINN 47 83 0 26 Jan 2020
Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach H. Hwang Jin Woo Jang Hyeontae Jo Jae Yong Lee 365 36 0 22 Nov 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 97 1,528 0 10 Jul 2019
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 119 1,387 0 30 Sep 2017
Imposing Hard Constraints on Deep Networks: Promises and Limitations Pablo Márquez-Neila Mathieu Salzmann Pascal Fua PINN UQCV 143 140 0 07 Jun 2017
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 323 18,613 0 06 Feb 2015