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Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations

2 August 2017

Papers citing "Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations"

50 / 318 papers shown

Title
Non-intrusive Nonlinear Model Reduction via Machine Learning Approximations to Low-dimensional Operators Zhe Bai Liqian Peng 31 12 0 17 Jun 2021
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation Rongye Shi Zhaobin Mo Kuang Huang Xuan Di Qi Du PINN 59 93 0 06 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 102 4 0 02 Jun 2021
Invertible Surrogate Models: Joint surrogate modelling and reconstruction of Laser-Wakefield Acceleration by invertible neural networks Friedrich Bethke R. Pausch Patrick Stiller A. Debus Michael Bussmann Nico Hoffmann 64 3 0 01 Jun 2021
OASIS: An Active Framework for Set Inversion Binh T. Nguyen D. M. Nguyen L. Ho Vu C. Dinh 13 5 0 31 May 2021
$Neural Network Training Using $\ell_1$-Regularization and Bi-fidelity Data$ Neural Network Training Using $\ell_1$ -Regularization and Bi-fidelity Data Subhayan De Alireza Doostan 71 25 0 27 May 2021
TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems Hai V. Nguyen T. Bui-Thanh PINN AI4CE 35 9 0 25 May 2021
Deep learning neural networks for the third-order nonlinear Schrodinger equation: Solitons, breathers, and rogue waves Zijian Zhou Zhenya Yan 130 34 0 30 Apr 2021
Distributed Multigrid Neural Solvers on Megavoxel Domains Aditya Balu Sergio Botelho Biswajit Khara Vinay Rao Chinmay Hegde Soumik Sarkar Santi S. Adavani A. Krishnamurthy Baskar Ganapathysubramanian AI4CE 110 11 0 29 Apr 2021
On the approximation of functions by tanh neural networks Tim De Ryck S. Lanthaler Siddhartha Mishra 58 140 0 18 Apr 2021
Geometry encoding for numerical simulations Amir Maleki J. Heyse Rishikesh Ranade Haiyang He Priya Kasimbeg Jay Pathak 3DV AI4CE 96 2 0 15 Apr 2021
A Latent space solver for PDE generalization Rishikesh Ranade C. Hill Haiyang He Amir Maleki Jay Pathak AI4CE 77 4 0 06 Apr 2021
Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and their Interface under Uncertainty using Machine Learning Subhayan De B. Hai Alireza Doostan M. Bause 30 2 0 30 Mar 2021
A Temporal Kernel Approach for Deep Learning with Continuous-time Information Da Xu Chuanwei Ruan Evren Körpeoglu Sushant Kumar Kannan Achan SyDa AI4TS 42 4 0 28 Mar 2021
Similarity-Based Equational Inference in Physics Jordan Meadows André Freitas 36 5 0 24 Mar 2021
The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation Q. Du Yiqi Gu Haizhao Yang Chao Zhou 66 20 0 21 Mar 2021
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps Ren-Chuen Chen Molei Tao 88 52 0 09 Mar 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 81 21 0 04 Mar 2021
Learning orbital dynamics of binary black hole systems from gravitational wave measurements B. Keith Akshay Khadse Scott E. Field 40 10 0 25 Feb 2021
Refinement of polygonal grids using Convolutional Neural Networks with applications to polygonal Discontinuous Galerkin and Virtual Element methods P. Antonietti E. Manuzzi 47 21 0 10 Feb 2021
On Theory-training Neural Networks to Infer the Solution of Highly Coupled Differential Equations M. T. Rad A. Viardin M. Apel AI4CE 32 3 0 09 Feb 2021
Physics-aware, deep probabilistic modeling of multiscale dynamics in the Small Data regime Sebastian Kaltenbach P. Koutsourelakis AI4CE 46 1 0 08 Feb 2021
A Deep Collocation Method for the Bending Analysis of Kirchhoff Plate Hongwei Guo X. Zhuang Timon Rabczuk AI4CE 60 439 0 04 Feb 2021
Learning elliptic partial differential equations with randomized linear algebra Nicolas Boullé Alex Townsend 40 43 0 31 Jan 2021
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition S. Fresca Andrea Manzoni AI4CE 69 219 0 28 Jan 2021
Physics-Informed Deep Learning for Traffic State Estimation Rongye Shi Zhaobin Mo Kuang Huang Xuan Di Qi Du AI4TS 31 0 0 17 Jan 2021
Data-driven peakon and periodic peakon travelling wave solutions of some nonlinear dispersive equations via deep learning Li Wang Zhenya Yan 110 48 0 12 Jan 2021
A Physics-Informed Deep Learning Paradigm for Car-Following Models Zhaobin Mo Xuan Di Rongye Shi PINN AI4CE 181 137 0 24 Dec 2020
Gaussian Process Regression constrained by Boundary Value Problems Mamikon A. Gulian A. Frankel L. Swiler 75 25 0 22 Dec 2020
Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning Li Wang Zhenya Yan 76 85 0 18 Dec 2020
SRoll3: A neural network approach to reduce large-scale systematic effects in the Planck High Frequency Instrument maps Manuel López-Radcenco J. Delouis L. Vibert 15 2 0 17 Dec 2020
A Data Driven Method for Computing Quasipotentials Bo Lin Qianxiao Li W. Ren 108 15 0 13 Dec 2020
Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems Ryan Lopez P. Atzberger DRL AI4CE 58 13 0 07 Dec 2020
Wide-band butterfly network: stable and efficient inversion via multi-frequency neural networks Matthew T.C. Li L. Demanet Leonardo Zepeda-Núnez 77 9 0 24 Nov 2020
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data Hao Xu Dongxiao Zhang Nanzhe Wang 82 34 0 24 Nov 2020
A Use of Even Activation Functions in Neural Networks Fuchang Gao Boyu Zhang 12 3 0 23 Nov 2020
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems Rui Wang Danielle C. Maddix Christos Faloutsos Bernie Wang Rose Yu OOD AI4CE 53 52 0 20 Nov 2020
On the equivalence of molecular graph convolution and molecular wave function with poor basis set Masashi Tsubaki T. Mizoguchi 28 9 0 16 Nov 2020
Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets Christian Soize R. Ghanem AI4CE 63 28 0 27 Oct 2020
Deep neural network for solving differential equations motivated by Legendre-Galerkin approximation Bryce Chudomelka Youngjoon Hong Hyunwoo J. Kim Jinyoung Park 69 7 0 24 Oct 2020
A Perspective on Machine Learning Methods in Turbulence Modelling Andrea Beck Marius Kurz AI4CE 81 101 0 23 Oct 2020
Exponential ReLU Neural Network Approximation Rates for Point and Edge Singularities C. Marcati J. Opschoor P. Petersen Christoph Schwab 71 30 0 23 Oct 2020
Data-driven Identification of 2D Partial Differential Equations using extracted physical features Kazem Meidani A. Farimani 54 17 0 20 Oct 2020
Energy-based error bound of physics-informed neural network solutions in elasticity Mengwu Guo E. Haghighat PINN 132 29 0 18 Oct 2020
Stochastic embeddings of dynamical phenomena through variational autoencoders C. A. García P. Félix J. Presedo A. Otero BDL 53 2 0 13 Oct 2020
Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems Jason D Miller Sui Tang Ming Zhong Mauro Maggioni 64 18 0 08 Oct 2020
Stochastic analysis of heterogeneous porous material with modified neural architecture search (NAS) based physics-informed neural networks using transfer learning Hongwei Guo X. Zhuang Timon Rabczuk 87 84 0 03 Oct 2020
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 63 16 0 28 Sep 2020
Physics Informed Neural Networks for Simulating Radiative Transfer Siddhartha Mishra Roberto Molinaro PINN 89 110 0 25 Sep 2020
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data Kadierdan Kaheman Steven L. Brunton J. Nathan Kutz 66 83 0 12 Sep 2020