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DeepXDE: A deep learning library for solving differential equations

10 July 2019

Papers citing "DeepXDE: A deep learning library for solving differential equations"

50 / 484 papers shown

Title
IDRLnet: A Physics-Informed Neural Network Library Wei Peng Jun Zhang Weien Zhou Xiaoyu Zhao Wen Yao Xiaoqian Chen PINN AI4CE 84 16 0 09 Jul 2021
Cell-average based neural network method for hyperbolic and parabolic partial differential equations Changxin Qiu Jue Yan 64 10 0 02 Jul 2021
Error analysis for physics informed neural networks (PINNs) approximating Kolmogorov PDEs Tim De Ryck Siddhartha Mishra PINN 99 103 0 28 Jun 2021
Legendre Deep Neural Network (LDNN) and its application for approximation of nonlinear Volterra Fredholm Hammerstein integral equations Z. Hajimohammadi Kourosh Parand A. Ghodsi 51 5 0 27 Jun 2021
PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs Pu Ren Chengping Rao Yang Liu Jianxun Wang Hao Sun DiffM AI4CE 136 206 0 26 Jun 2021
Lagrangian dual framework for conservative neural network solutions of kinetic equations H. Hwang Hwijae Son 74 8 0 23 Jun 2021
Approximation capabilities of measure-preserving neural networks Aiqing Zhu Pengzhan Jin Yifa Tang 84 8 0 21 Jun 2021
Long-time integration of parametric evolution equations with physics-informed DeepONets Sizhuang He P. Perdikaris AI4CE 89 122 0 09 Jun 2021
Choose a Transformer: Fourier or Galerkin Shuhao Cao 90 256 0 31 May 2021
TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems Hai V. Nguyen T. Bui-Thanh PINN AI4CE 48 10 0 25 May 2021
Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver Yuankai Teng Xiaoping Zhang Zhu Wang L. Ju 90 14 0 23 May 2021
BubbleNet: Inferring micro-bubble dynamics with semi-physics-informed deep learning Hanfeng Zhai Quan Zhou G. Hu PINN AI4CE 63 16 0 15 May 2021
On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems Wagner Gonçalves Pinto Antonio Alguacil Michaël Bauerheim 41 2 0 12 May 2021
ReLU Deep Neural Networks from the Hierarchical Basis Perspective Juncai He Lin Li Jinchao Xu AI4CE 59 30 0 10 May 2021
Data-driven discovery of Green's functions with human-understandable deep learning Nicolas Boullé Christopher Earls Alex Townsend PINN AI4CE 60 60 0 01 May 2021
Deep learning neural networks for the third-order nonlinear Schrodinger equation: Solitons, breathers, and rogue waves Zijian Zhou Zhenya Yan 137 34 0 30 Apr 2021
Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks N. Sukumar Ankit Srivastava PINN AI4CE 157 255 0 17 Apr 2021
Applications of physics-informed scientific machine learning in subsurface science: A survey A. Sun H. Yoon C. Shih Zhi Zhong AI4CE 82 11 0 10 Apr 2021
Conditional physics informed neural networks A. Kovacs L. Exl Alexander Kornell J. Fischbacher Markus Hovorka ... N. Sakuma Akihito Kinoshita T. Shoji A. Kato T. Schrefl PINN 70 44 0 06 Apr 2021
One-shot learning for solution operators of partial differential equations Priya Kasimbeg Haiyang He Rishikesh Ranade Jay Pathak Lu Lu AI4CE 97 12 0 06 Apr 2021
Distributional Offline Continuous-Time Reinforcement Learning with Neural Physics-Informed PDEs (SciPhy RL for DOCTR-L) I. Halperin OffRL 70 7 0 02 Apr 2021
Deep Learning of Conjugate Mappings J. Bramburger S. Patterson J. Nathan Kutz 75 15 0 01 Apr 2021
dNNsolve: an efficient NN-based PDE solver V. Guidetti F. Muia Y. Welling A. Westphal 50 6 0 15 Mar 2021
The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? Stefano Markidis PINN 75 193 0 12 Mar 2021
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran PINN AI4CE 144 80 0 25 Feb 2021
NTopo: Mesh-free Topology Optimization using Implicit Neural Representations Jonas Zehnder Yue Li Stelian Coros B. Thomaszewski AI4CE 80 61 0 22 Feb 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 102 522 0 09 Feb 2021
Inferring incompressible two-phase flow fields from the interface motion using physics-informed neural networks Aaron B. Buhendwa Stefan Adami Nikolaus A. Adams AI4CE PINN 50 35 0 25 Jan 2021
A Taylor Based Sampling Scheme for Machine Learning in Computational Physics Paul Novello Gaël Poëtte D. Lugato P. Congedo PINN AI4CE 127 0 0 20 Jan 2021
Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification L. Scarabosio 84 9 0 18 Jan 2021
Data-driven discovery of multiscale chemical reactions governed by the law of mass action Juntao Huang Y. Zhou W. Yong 52 6 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 115 48 0 12 Jan 2021
Constrained Block Nonlinear Neural Dynamical Models Elliott Skomski Soumya Vasisht Colby Wight Aaron Tuor Ján Drgoňa D. Vrabie AI4CE 112 16 0 06 Jan 2021
Learning emergent PDEs in a learned emergent space Felix P. Kemeth Tom S. Bertalan Thomas Thiem Felix Dietrich S. Moon C. Laing Ioannis G. Kevrekidis AI4CE 34 7 0 23 Dec 2020
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 121 153 0 22 Dec 2020
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 146 130 0 14 Dec 2020
Algorithmically-Consistent Deep Learning Frameworks for Structural Topology Optimization Jaydeep Rade Aditya Balu Ethan Herron Jay Pathak Rishikesh Ranade Soumik Sarkar A. Krishnamurthy 54 44 0 09 Dec 2020
Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture S. Niaki E. Haghighat Trevor Campbell Xinglong Li R. Vaziri AI4CE 142 211 0 27 Nov 2020
On the application of Physically-Guided Neural Networks with Internal Variables to Continuum Problems J. Ayensa-Jiménez M. H. Doweidar J. A. Sanz-Herrera Manuel Doblaré 33 1 0 23 Nov 2020
MGIC: Multigrid-in-Channels Neural Network Architectures Moshe Eliasof Jonathan Ephrath Lars Ruthotto Eran Treister 109 8 0 17 Nov 2020
Texture image classification based on a pseudo-parabolic diffusion model Jardel Vieira E. Abreu J. Florindo DiffM 38 7 0 14 Nov 2020
Efficient nonlinear manifold reduced order model Youngkyu Kim Youngsoo Choi David Widemann T. Zohdi 74 43 0 13 Nov 2020
Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics Ján Drgoňa Aaron Tuor V. Chandan D. Vrabie AI4CE 89 121 0 11 Nov 2020
Physics-informed Neural-Network Software for Molecular Dynamics Applications Taufeq Mohammed Razakh Beibei Wang Shane Jackson R. Kalia A. Nakano K. Nomura P. Vashishta PINN 66 11 0 06 Nov 2020
Frequency-compensated PINNs for Fluid-dynamic Design Problems Tongtao Zhang Biswadip Dey P. Kakkar A. Dasgupta Amit Chakraborty PINN AI4CE 52 9 0 03 Nov 2020
Exponential ReLU Neural Network Approximation Rates for Point and Edge Singularities C. Marcati J. Opschoor P. Petersen Christoph Schwab 79 30 0 23 Oct 2020
Data-driven Identification of 2D Partial Differential Equations using extracted physical features Kazem Meidani A. Farimani 64 17 0 20 Oct 2020
Living in the Physics and Machine Learning Interplay for Earth Observation Gustau Camps-Valls D. Svendsen Jordi Cortés-Andrés Álvaro Moreno-Martínez Adrián Pérez-Suay J. Adsuara I. Martín M. Piles Jordi Munoz-Marí Luca Martino PINN AI4CE 41 6 0 18 Oct 2020
Deep FPF: Gain function approximation in high-dimensional setting S. Y. Olmez Amirhossein Taghvaei P. Mehta 77 9 0 02 Oct 2020
The model reduction of the Vlasov-Poisson-Fokker-Planck system to the Poisson-Nernst-Planck system via the Deep Neural Network Approach Jae Yong Lee Jin Woo Jang H. Hwang 40 13 0 28 Sep 2020