Quantifying total uncertainty in physics-informed neural networks for
solving forward and inverse stochastic problems

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

21 September 2018

George Karniadakis

Papers citing "Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems"

13 / 63 papers shown

Title
Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications Yating Wang Wei Deng Guang Lin 18 13 0 29 Jun 2020
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao Sun Yang Liu PINN AI4CE 17 222 0 10 Jun 2020
Learning on dynamic statistical manifolds F. Boso D. Tartakovsky 27 10 0 07 May 2020
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations Christopher J. Arthurs A. King PINN 40 51 0 02 May 2020
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems Pengzhan Jin Zhen Zhang Aiqing Zhu Yifa Tang George Karniadakis 21 21 0 11 Jan 2020
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs Liu Yang Sean Treichler Thorsten Kurth Keno Fischer D. Barajas-Solano ... Valentin Churavy A. Tartakovsky Michael Houston P. Prabhat George Karniadakis AI4CE 47 38 0 29 Oct 2019
Deep Learning of Subsurface Flow via Theory-guided Neural Network Nanzhe Wang Dongxiao Zhang Haibin Chang Heng Li AI4CE 30 226 0 24 Oct 2019
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng Zhen Li Dongkun Zhang George Karniadakis PINN AI4CE 22 442 0 23 Sep 2019
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data Hao Xu Haibin Chang Dongxiao Zhang AI4CE 14 69 0 13 Aug 2019
Distributed physics informed neural network for data-efficient solution to partial differential equations Vikas Dwivedi N. Parashar Balaji Srinivasan PINN 13 81 0 21 Jul 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 31 1,485 0 10 Jul 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012