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"

47 / 297 papers shown

Title
Fast Modeling and Understanding Fluid Dynamics Systems with Encoder-Decoder Networks Rohan Thavarajah X. Zhai Zhe-Rui Ma D. Castineira PINN AI4CE 6 8 0 09 Jun 2020
Multi-fidelity Generative Deep Learning Turbulent Flows N. Geneva N. Zabaras AI4CE 6 44 0 08 Jun 2020
Deep learning of free boundary and Stefan problems Sifan Wang P. Perdikaris 6 80 0 04 Jun 2020
A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables Maximilian Rixner P. Koutsourelakis AI4CE 6 17 0 02 Jun 2020
Deep Learning of Dynamic Subsurface Flow via Theory-guided Generative Adversarial Network Tianhao He Dongxiao Zhang AI4CE 14 8 0 02 Jun 2020
Transfer learning based multi-fidelity physics informed deep neural network S. Chakraborty PINN OOD AI4CE 7 162 0 19 May 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 33 121 0 17 May 2020
A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural Networks Hao Ma Xiangyu Y. Hu Yuxuan Zhang Nils Thuerey O. Haidn AI4CE 13 12 0 16 May 2020
Learning Composable Energy Surrogates for PDE Order Reduction Alex Beatson Jordan T. Ash Geoffrey Roeder Tianju Xue Ryan P. Adams AI4CE 12 15 0 13 May 2020
Learning on dynamic statistical manifolds F. Boso D. Tartakovsky 11 10 0 07 May 2020
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh P. Bremer J. Gaffney G. Anderson B. Spears 8 21 0 05 May 2020
Simulation free reliability analysis: A physics-informed deep learning based approach S. Chakraborty AI4CE 9 16 0 04 May 2020
A Dual-Dimer Method for Training Physics-Constrained Neural Networks with Minimax Architecture Dehao Liu Yan Wang 6 71 0 01 May 2020
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network Nanzhe Wang Haibin Chang Dongxiao Zhang 18 59 0 25 Apr 2020
Bayesian differential programming for robust systems identification under uncertainty Yibo Yang Mohamed Aziz Bhouri P. Perdikaris OOD 12 32 0 15 Apr 2020
A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks Kun Wang WaiChing Sun Q. Du 6 22 0 13 Apr 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 80 385 0 10 Mar 2020
Physics-informed deep learning for incompressible laminar flows Chengping Rao Hao-Lun Sun Yang Liu PINN AI4CE 9 222 0 24 Feb 2020
A deep learning framework for solution and discovery in solid mechanics E. Haghighat M. Raissi A. Moure H. Gómez R. Juanes AI4CE PINN 6 56 0 14 Feb 2020
A Derivative-Free Method for Solving Elliptic Partial Differential Equations with Deep Neural Networks Jihun Han Mihai Nica A. Stinchcombe 14 49 0 17 Jan 2020
Physics Informed Deep Learning for Transport in Porous Media. Buckley Leverett Problem Cedric G. Fraces Adrien Papaioannou H. Tchelepi AI4CE PINN 14 19 0 15 Jan 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sifan Wang Yujun Teng P. Perdikaris AI4CE PINN 8 289 0 13 Jan 2020
Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines Panagiotis Tsilifis I. Papaioannou D. Štraub F. Nobile 13 18 0 23 Dec 2019
Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies Rushil Anirudh Jayaraman J. Thiagarajan P. Bremer B. Spears AI4CE 8 40 0 17 Dec 2019
VarNet: Variational Neural Networks for the Solution of Partial Differential Equations Reza Khodayi-mehr Michael M. Zavlanos 13 64 0 16 Dec 2019
Coercing Machine Learning to Output Physically Accurate Results Z. Geng Dan Johnson Ronald Fedkiw 3DH 13 37 0 21 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 23 1,980 0 08 Oct 2019
Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion Rushil Anirudh Kyong Hwan Jin Shusen Liu P. Bremer M. Stuber PINN AI4CE 11 0 0 03 Oct 2019
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models Teo Deveney Amelia Gosse Peter Du 15 9 0 03 Oct 2019
D3M: A deep domain decomposition method for partial differential equations Ke Li Keju Tang Tianfan Wu Qifeng Liao AI4CE 9 113 0 24 Sep 2019
Physics-informed semantic inpainting: Application to geostatistical modeling Q. Zheng L. Zeng Zhendan Cao George Karniadakis GAN 8 54 0 19 Sep 2019
Neural reparameterization improves structural optimization Stephan Hoyer Jascha Narain Sohl-Dickstein S. Greydanus AI4CE 11 67 0 10 Sep 2019
Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing M. Mudunuru S. Karra 14 10 0 28 Aug 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 14 1,466 0 10 Jul 2019
$Transfer learning enhanced physics informed neural network for phase-field modeling of fracture$ Transfer learning enhanced physics informed neural network for phase-field modeling of fracture S. Goswami C. Anitescu S. Chakraborty Timon Rabczuk PINN 22 588 0 04 Jul 2019
Integration of adversarial autoencoders with residual dense convolutional networks for estimation of non-Gaussian hydraulic conductivities S. Mo N. Zabaras Xiaoqing Shi Jichun Wu 8 43 0 26 Jun 2019
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM A. Chattopadhyay P. Hassanzadeh D. Subramanian AI4CE 8 40 0 20 Jun 2019
Modeling the Dynamics of PDE Systems with Physics-Constrained Deep Auto-Regressive Networks N. Geneva N. Zabaras AI4CE 10 265 0 13 Jun 2019
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability Shaowu Pan Karthik Duraisamy 10 134 0 09 Jun 2019
Encoding Invariances in Deep Generative Models Viraj Shah Ameya Joshi Sambuddha Ghosal B. Pokuri S. Sarkar Baskar Ganapathysubramanian C. Hegde PINN GAN 11 30 0 04 Jun 2019
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks Georgios Kissas Yibo Yang E. Hwuang W. Witschey John A. Detre P. Perdikaris AI4CE 13 364 0 13 May 2019
Variational training of neural network approximations of solution maps for physical models Yingzhou Li Jianfeng Lu Anqi Mao GAN 17 35 0 07 May 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 17 615 0 29 Mar 2019
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime Constantin Grigo P. Koutsourelakis AI4CE 6 25 0 11 Feb 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,568 0 09 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015