ST-PINN: A Self-Training Physics-Informed Neural Network for Partial
Differential Equations

ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations

15 June 2023

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Papers citing "ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations"

15 / 15 papers shown

Title
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning M. Takamoto T. Praditia Raphael Leiteritz Dan MacKinlay Francesco Alesiani Dirk Pflüger Mathias Niepert AI4CE 106 237 0 13 Oct 2022
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 99 383 0 21 Jul 2022
Generic bounds on the approximation error for physics-informed (and) operator learning Tim De Ryck Siddhartha Mishra PINN 121 62 0 23 May 2022
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 89 470 0 01 Nov 2021
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision Xiaokang Chen Yuhui Yuan Gang Zeng Jingdong Wang 103 786 0 02 Jun 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 88 1,209 0 20 May 2021
Physics-informed Spline Learning for Nonlinear Dynamics Discovery Fangzheng Sun Yang Liu Hao Sun AI4CE 51 28 0 05 May 2021
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D Nils Wandel Michael Weinmann Reinhard Klein AI4CE 77 51 0 22 Dec 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 141 924 0 28 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating a class of inverse problems for PDEs Siddhartha Mishra Roberto Molinaro PINN 94 267 0 29 Jun 2020
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning Sungyong Seo Chuizheng Meng Sirisha Rambhatla Yan Liu AI4CE 87 11 0 15 Jun 2020
Rethinking Pre-training and Self-training Barret Zoph Golnaz Ghiasi Nayeon Lee Huayu Chen Hanxiao Liu E. D. Cubuk Quoc V. Le SSeg 108 652 0 11 Jun 2020
On the convergence of physics informed neural networks for linear second-order elliptic and parabolic type PDEs Yeonjong Shin Jérome Darbon George Karniadakis PINN 71 79 0 03 Apr 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 243 793 0 13 Mar 2020
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 101 1,549 0 10 Jul 2019

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