Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

28 November 2017

Papers citing "Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations"

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Title
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 134 1,293 0 14 Jan 2022
An application of the splitting-up method for the computation of a neural network representation for the solution for the filtering equations Dan Crisan Alexander Lobbe S. Ortiz-Latorre 57 4 0 10 Jan 2022
Deep neural networks for smooth approximation of physics with higher order and continuity B-spline base functions Kamil Doleglo Anna Paszyñska Maciej Paszyñski L. Demkowicz 19 5 0 03 Jan 2022
Learned Coarse Models for Efficient Turbulence Simulation Kimberly L. Stachenfeld D. Fielding Dmitrii Kochkov M. Cranmer Tobias Pfaff Jonathan Godwin Can Cui S. Ho Peter W. Battaglia Alvaro Sanchez-Gonzalez AI4CE 117 84 0 31 Dec 2021
Total Energy Shaping with Neural Interconnection and Damping Assignment -- Passivity Based Control Santiago Sanchez-Escalonilla Rodolfo Reyes-Báez B. Jayawardhana 75 9 0 24 Dec 2021
Multigoal-oriented dual-weighted-residual error estimation using deep neural networks Ayan Chakraborty T. Wick X. Zhuang Timon Rabczuk 52 8 0 21 Dec 2021
Physics-informed neural network method for modelling beam-wall interactions K. Fujita AI4CE 21 5 0 21 Dec 2021
Machine Learning-Accelerated Computational Solid Mechanics: Application to Linear Elasticity Rajat Arora AI4CE 108 7 0 16 Dec 2021
Domain-informed neural networks for interaction localization within astroparticle experiments Shixiao Liang A. Higuera C. Peters Venkat Roy W. Bajwa H. Shatkay C. Tunnell 71 7 0 15 Dec 2021
Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems Nikolas Nusken Lorenz Richter PINN DiffM 100 30 0 07 Dec 2021
Physically Consistent Neural Networks for building thermal modeling: theory and analysis L. D. Natale B. Svetozarevic Philipp Heer Colin N. Jones PINN AI4CE 107 90 0 06 Dec 2021
Physics-informed Evolutionary Strategy based Control for Mitigating Delayed Voltage Recovery Yan Du Qiuhua Huang Renke Huang Tianzhixi Yin Jie Tan Wenhao Yu Xinya Li 39 14 0 29 Nov 2021
Neural Symplectic Integrator with Hamiltonian Inductive Bias for the Gravitational $N$ -body Problem Maxwell X. Cai Simon Portegies Zwart Damian Podareanu PINN 44 3 0 28 Nov 2021
Residual fourier neural operator for thermochemical curing of composites Gengxiang Chen Yingguang Li Xu Liu Qinglu Meng Jing Zhou Xiaozhong Hao AI4CE 133 7 0 15 Nov 2021
NeuralPDE: Modelling Dynamical Systems from Data Andrzej Dulny Andreas Hotho Anna Krause AI4CE 57 11 0 15 Nov 2021
On the Stochastic Stability of Deep Markov Models Ján Drgoňa Sayak Mukherjee Jiaxin Zhang Frank Liu M. Halappanavar BDL 51 6 0 08 Nov 2021
Numerical Approximation in CFD Problems Using Physics Informed Machine Learning Siddharth Rout Vikas Dwivedi Balaji Srinivasan PINN 16 2 0 01 Nov 2021
Towards Comparative Physical Interpretation of Spatial Variability Aware Neural Networks: A Summary of Results Jayant Gupta Carl Molnar Gaoxiang Luo Joe Knight Shashi Shekhar 16 0 0 29 Oct 2021
Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN Hamza Boukraichi N. Akkari F. Casenave David Ryckelynck AI4CE 38 3 0 26 Oct 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 105 45 0 26 Oct 2021
Error-correcting neural networks for semi-Lagrangian advection in the level-set method Luis Ángel Larios-Cárdenas Frédéric Gibou 39 7 0 22 Oct 2021
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 97 42 0 05 Oct 2021
Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning Ziming Liu Yunyue Chen Yuanqi Du Max Tegmark PINN AI4CE 91 22 0 28 Sep 2021
Lyapunov-Net: A Deep Neural Network Architecture for Lyapunov Function Approximation Nathan Gaby Fumin Zhang X. Ye PINN 72 41 0 27 Sep 2021
Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations Li Cheng Ekhi Ajuria Illarramendi Guillaume Bogopolsky M. Bauerheim B. Cuenot 80 19 0 27 Sep 2021
Performance and accuracy assessments of an incompressible fluid solver coupled with a deep Convolutional Neural Network Ekhi Ajuria Illarramendi M. Bauerheim B. Cuenot 89 21 0 20 Sep 2021
Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models Ling Guo Hao Wu Tao Zhou AI4CE 77 48 0 30 Aug 2021
ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting Yu Huang James Li Min Shi H. Zhuang Xingquan Zhu Laurent Chérubin James H. VanZwieten Yufei Tang AI4CE PINN 45 6 0 12 Aug 2021
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems Shaan Desai M. Mattheakis David Sondak P. Protopapas Stephen J. Roberts AI4CE 97 47 0 16 Jul 2021
Estimating Counts Through an Average Rounded to the Nearest Non-negative Integer and its Theoretical & Practical Effects R. Rivera Axel Cortes-Cubero Roberto Reyes-Carranza W. Rolke 17 0 0 04 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 96 69 0 02 Jul 2021
Multifidelity Modeling for Physics-Informed Neural Networks (PINNs) Michael Penwarden Shandian Zhe A. Narayan Robert M. Kirby 99 46 0 25 Jun 2021
Physics perception in sloshing scenes with guaranteed thermodynamic consistency B. Moya Alberto Badías D. González Francisco Chinesta Elías Cueto 74 14 0 24 Jun 2021
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks Shibo Li Robert M. Kirby Shandian Zhe 77 13 0 18 Jun 2021
Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling Niv Giladi Z. Ben-Haim Sella Nevo Yossi Matias Daniel Soudry AI4CE 52 9 0 14 Jun 2021
Learning Full Configuration Interaction Electron Correlations with Deep Learning H. Corzo Arijit Sehanobish Onur Kara 29 2 0 08 Jun 2021
Encoding Involutory Invariances in Neural Networks Anwesh Bhattacharya M. Mattheakis P. Protopapas 93 1 0 07 Jun 2021
Deep Neural Network Modeling of Unknown Partial Differential Equations in Nodal Space Zhen Chen V. Churchill Kailiang Wu D. Xiu AI4CE 53 48 0 07 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
Data-Driven Shadowgraph Simulation of a 3D Object Anna Willmann Patrick Stiller A. Debus A. Irman R. Pausch Yen-Yu Chang Michael Bussmann Nico Hoffmann 40 3 0 01 Jun 2021
Empirical Models for Multidimensional Regression of Fission Systems A. Dave Jiankai Yu Jarod N Wilson B. Phillips K. Sun Benoit Forget 39 1 0 30 May 2021
Deep Hierarchical Super Resolution for Scientific Data Skylar W. Wurster Hanqi Guo Han-Wei Shen T. Peterka Jiayi Xu 75 13 0 30 May 2021
Least-Squares ReLU Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Law Z. Cai Jingshuang Chen Min Liu PINN 55 25 0 25 May 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 96 1,213 0 20 May 2021
Physics-informed attention-based neural network for solving non-linear partial differential equations R. Torrado Pablo Ruiz L. Cueto‐Felgueroso M. Green Tyler Friesen S. Matringe Julian Togelius PINN 63 12 0 17 May 2021
BubbleNet: Inferring micro-bubble dynamics with semi-physics-informed deep learning Hanfeng Zhai Quan Zhou G. Hu PINN AI4CE 39 16 0 15 May 2021
Value Iteration in Continuous Actions, States and Time M. Lutter Shie Mannor Jan Peters Dieter Fox Animesh Garg 52 37 0 10 May 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 46 22 0 07 May 2021
Neural graphical modelling in continuous-time: consistency guarantees and algorithms Alexis Bellot K. Branson M. Schaar CML AI4TS 91 46 0 06 May 2021
Personalized Algorithm Generation: A Case Study in Learning ODE Integrators Yue Guo Felix Dietrich Tom S. Bertalan Danimir T. Doncevic Manuel Dahmen Ioannis G. Kevrekidis Qianxiao Li 77 11 0 04 May 2021