Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data

18 January 2019

Papers citing "Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data"

50 / 297 papers shown

Title
Integration of knowledge and data in machine learning Yuntian Chen Dongxiao Zhang PINN 28 31 0 15 Feb 2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 25 40 0 09 Feb 2022
Physics-informed neural networks for solving parametric magnetostatic problems Andrés Beltrán-Pulido Ilias Bilionis D. Aliprantis 24 34 0 08 Feb 2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Mathilde Mougeot PINN AI4CE 81 29 0 31 Jan 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 43 27 0 28 Jan 2022
Pseudo-Differential Neural Operator: Generalized Fourier Neural Operator for Learning Solution Operators of Partial Differential Equations J. Shin Jae Yong Lee H. Hwang 24 2 0 28 Jan 2022
Physics-informed ConvNet: Learning Physical Field from a Shallow Neural Network Peng Shi Zhi Zeng Tianshou Liang AI4CE 26 20 0 26 Jan 2022
Heat Conduction Plate Layout Optimization using Physics-driven Convolutional Neural Networks Hao Ma Yang-Tian Sun M. Chiarelli 26 2 0 21 Jan 2022
Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification A. Thakur S. Chakraborty MedIm 31 4 0 19 Jan 2022
Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks Xu Liu Wei Peng Zhiqiang Gong Weien Zhou W. Yao 19 54 0 18 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,179 0 14 Jan 2022
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations Keju Tang Xiaoliang Wan Chao Yang 19 107 0 28 Dec 2021
Solving time dependent Fokker-Planck equations via temporal normalizing flow Xiaodong Feng Li Zeng Tao Zhou AI4CE 36 25 0 28 Dec 2021
Curriculum learning for data-driven modeling of dynamical systems Alessandro Bucci Onofrio Semeraro A. Allauzen S. Chibbaro L. Mathelin PINN AI4CE 27 7 0 15 Dec 2021
Physics-enhanced Neural Networks in the Small Data Regime Jonas Eichelsdörfer Sebastian Kaltenbach P. Koutsourelakis AI4CE PINN 14 5 0 19 Nov 2021
Using Computational Intelligence for solving the Ornstein-Zernike equation Edwin Bedolla 16 0 0 17 Nov 2021
Uncertainty quantification and inverse modeling for subsurface flow in 3D heterogeneous formations using a theory-guided convolutional encoder-decoder network Rui Xu Dongxiao Zhang Nanzhe Wang AI4CE 31 17 0 14 Nov 2021
Solving PDE-constrained Control Problems Using Operator Learning Rakhoon Hwang Jae Yong Lee J. Shin H. Hwang AI4CE 117 43 0 09 Nov 2021
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 62 384 0 06 Nov 2021
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method Zhongjian Wang Jack Xin Zhiwen Zhang 39 15 0 02 Nov 2021
Uncertainty quantification for ptychography using normalizing flows Agnimitra Dasgupta Z. Di AI4CE 28 5 0 01 Nov 2021
A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs Michael Penwarden Shandian Zhe A. Narayan Robert M. Kirby PINN AI4CE 25 39 0 26 Oct 2021
Interpretable AI forecasting for numerical relativity waveforms of quasi-circular, spinning, non-precessing binary black hole mergers Asad Khan Eliu A. Huerta Huihuo Zheng 21 11 0 13 Oct 2021
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network Nanzhe Wang Haibin Chang Dongxiao Zhang 14 34 0 12 Oct 2021
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 25 152 0 09 Oct 2021
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs Biswajit Khara Aditya Balu Ameya Joshi S. Sarkar C. Hegde A. Krishnamurthy Baskar Ganapathysubramanian 26 19 0 04 Oct 2021
Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion S. Basir Inanc Senocak PINN AI4CE 34 68 0 30 Sep 2021
slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks Elizabeth Newman Julianne Chung Matthias Chung Lars Ruthotto 47 6 0 28 Sep 2021
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data Xiaoyu Zhao Zhiqiang Gong Yunyang Zhang Wen Yao Xiaoqian Chen OOD AI4CE 77 91 0 26 Sep 2021
PCNN: A physics-constrained neural network for multiphase flows Haoyang Zheng Ziyang Huang Guang Lin PINN 24 8 0 18 Sep 2021
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 58 60 0 15 Sep 2021
Reconstructing High-resolution Turbulent Flows Using Physics-Guided Neural Networks Shengyu Chen S. Sammak P. Givi J. Yurko Xiaowei Jia AI4CE 27 9 0 06 Sep 2021
U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow Gege Wen Zong-Yi Li Kamyar Azizzadenesheli Anima Anandkumar S. Benson AI4CE 34 366 0 03 Sep 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 36 610 0 02 Sep 2021
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems Shailesh Garg S. Chakraborty B. Hazra 46 20 0 01 Sep 2021
GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations Y. Kumar S. Chakraborty 19 8 0 24 Aug 2021
Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning Sayan Ghosh G. A. Padmanabha Cheng Peng Steven Atkinson Valeria Andreoli Piyush Pandita T. Vandeputte N. Zabaras Liping Wang AI4CE 33 13 0 17 Aug 2021
Physics-constrained Deep Learning for Robust Inverse ECG Modeling Jianxin Xie B. Yao 30 21 0 26 Jul 2021
Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings B. Bahmani WaiChing Sun PINN AI4CE 31 17 0 24 Jul 2021
A novel meta-learning initialization method for physics-informed neural networks Xu Liu Xiaoya Zhang Wei Peng Weien Zhou W. Yao AI4CE 22 72 0 23 Jul 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 45 209 0 16 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 65 0 02 Jul 2021
PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs Pu Ren Chengping Rao Yang Liu Jianxun Wang Hao Sun DiffM AI4CE 39 192 0 26 Jun 2021
Joint Deep Reversible Regression Model and Physics-Informed Unsupervised Learning for Temperature Field Reconstruction Zhiqiang Gong Weien Zhou Jun Zhang Wei Peng W. Yao AI4CE 39 11 0 22 Jun 2021
Making Invisible Visible: Data-Driven Seismic Inversion with Spatio-temporally Constrained Data Augmentation Yuxin Yang Xitong Zhang Qiang Guan Youzuo Lin 30 15 0 22 Jun 2021
Long-time integration of parametric evolution equations with physics-informed DeepONets Sizhuang He P. Perdikaris AI4CE 24 117 0 09 Jun 2021
Encoding physics to learn reaction-diffusion processes Chengping Rao Pu Ren Qi Wang O. Buyukozturk Haoqin Sun Yang Liu PINN AI4CE DiffM 30 78 0 09 Jun 2021
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reduction Tiangang Cui S. Dolgov O. Zahm 24 15 0 08 Jun 2021
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations Yingtao Luo Qiang Liu Yuntian Chen Wenbo Hu Tian Tian Jun Zhu DiffM 50 4 0 02 Jun 2021
Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver Yuankai Teng Xiaoping Zhang Zhu Wang L. Ju 13 14 0 23 May 2021