DeepXDE: A deep learning library for solving differential equations

10 July 2019

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

50 / 483 papers shown

Title
Accurate and Fast Fischer-Tropsch Reaction Microkinetics using PINNs Harshil Patel Aniruddha Panda T. Nikolaienko Stanislav Jaso Alejandro Lopez Kaushic Kalyanaraman 36 2 0 17 Nov 2023
Moving Sampling Physics-informed Neural Networks induced by Moving Mesh PDE Yu Yang Qihong Yang Yangtao Deng Qiaolin He 11 3 0 14 Nov 2023
Solution of FPK Equation for Stochastic Dynamics Subjected to Additive Gaussian Noise via Deep Learning Approach Amir H. Khodabakhsh S. Pourtakdoust 21 7 0 08 Nov 2023
Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework Dashan Zhang Yuntian Chen Shiyi Chen AI4CE 32 2 0 07 Nov 2023
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations Valentin Duruisseaux Amit Chakraborty AI4CE 18 1 0 04 Nov 2023
Data-Driven Model Selections of Second-Order Particle Dynamics via Integrating Gaussian Processes with Low-Dimensional Interacting Structures Jinchao Feng Charles Kulick Sui Tang 29 2 0 01 Nov 2023
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator Learning Kuangdai Leng Mallikarjun Shankar Jeyan Thiyagalingam 34 2 0 01 Nov 2023
A hybrid approach for solving the gravitational N-body problem with Artificial Neural Networks V. S. Ulibarrena Philipp Horn S. P. Zwart E. Sellentin B. Koren Maxwell X. Cai PINN 22 2 0 31 Oct 2023
Adaptive importance sampling for Deep Ritz Xiaoliang Wan Tao Zhou Yuancheng Zhou 29 2 0 26 Oct 2023
Adversarial Training for Physics-Informed Neural Networks Yao Li Shengzhu Shi Zhichang Guo Boying Wu AAML PINN 30 0 0 18 Oct 2023
Correcting model misspecification in physics-informed neural networks (PINNs) Zongren Zou Xuhui Meng George Karniadakis PINN 29 41 0 16 Oct 2023
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction Lanxiang Xing Haixu Wu Yuezhou Ma Jianmin Wang Mingsheng Long MDE AI4CE 32 4 0 16 Oct 2023
Time integration schemes based on neural networks for solving partial differential equations on coarse grids Xinxin Yan Zhideng Zhou Xiaohan Cheng Xiaolei Yang AI4TS AI4CE 17 0 0 16 Oct 2023
HNS: An Efficient Hermite Neural Solver for Solving Time-Fractional Partial Differential Equations Jie Hou Zhiying Ma Shihui Ying Ying Li 14 5 0 07 Oct 2023
Spectral operator learning for parametric PDEs without data reliance Junho Choi Taehyun Yun Namjung Kim Youngjoon Hong 27 8 0 03 Oct 2023
On Training Derivative-Constrained Neural Networks KaiChieh Lo Daniel Huang 31 3 0 02 Oct 2023
Deep learning soliton dynamics and complex potentials recognition for 1D and 2D PT-symmetric saturable nonlinear Schrödinger equations Jin Song Ilya Shenbin 89 25 0 29 Sep 2023
Data-driven localized waves and parameter discovery in the massive Thirring model via extended physics-informed neural networks with interface zones Christian Berger Sadok Ben Toumia Zijian Zhou Zhenya Yan PINN 28 8 0 29 Sep 2023
Comparing Active Learning Performance Driven by Gaussian Processes or Bayesian Neural Networks for Constrained Trajectory Exploration Sapphira Akins Frances Zhu 19 1 0 28 Sep 2023
Exciton-Polariton Condensates: A Fourier Neural Operator Approach S. T. Sathujoda Yuan Wang Kanishk Gandhi 27 0 0 27 Sep 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 43 0 0 27 Sep 2023
Physics Informed Neural Network Code for 2D Transient Problems (PINN-2DT) Compatible with Google Colab Pawel Maczuga Maciej Sikora Maciej Skoczeñ Przemyslaw Ro.znawski Filip Tluszcz Marcin Szubert Marcin Lo's W. Dzwinel K. Pingali Maciej Paszyñski AI4CE 30 0 0 24 Sep 2023
Multi-Grade Deep Learning for Partial Differential Equations with Applications to the Burgers Equation Yuesheng Xu Taishan Zeng AI4CE 32 4 0 14 Sep 2023
An Extreme Learning Machine-Based Method for Computational PDEs in Higher Dimensions Yiran Wang Suchuan Dong 31 35 0 13 Sep 2023
Physics-Informed Polynomial Chaos Expansions Lukávs Novák Himanshu Sharma Michael D. Shields 25 15 0 04 Sep 2023
Physics-inspired Neural Networks for Parameter Learning of Adaptive Cruise Control Systems Theocharis Apostolakis K. Ampountolas 19 5 0 03 Sep 2023
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning Qian Zhang Chen-Chun Wu Adar Kahana Youngeun Kim Yuhang Li George Karniadakis Priyadarshini Panda 33 9 0 31 Aug 2023
Identifying Constitutive Parameters for Complex Hyperelastic Materials using Physics-Informed Neural Networks Siyuan Song Hanxun Jin AI4CE PINN 25 6 0 29 Aug 2023
Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers Arthur Feeney Zitong Li Ramin Bostanabad Aparna Chandramowlishwaran AI4CE 16 1 0 28 Aug 2023
Bayesian Reasoning for Physics Informed Neural Networks K. Graczyk Kornel Witkowski 38 0 0 25 Aug 2023
Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks T. Şahin M. Danwitz A. Popp PINN 34 20 0 24 Aug 2023
Physics informed Neural Networks applied to the description of wave-particle resonance in kinetic simulations of fusion plasmas J. Kumar D. Zarzoso V. Grandgirard Jana Ebert Stefan Kesselheim PINN 27 0 0 23 Aug 2023
Reconstructing $S$ -matrix Phases with Machine Learning Aurélien Dersy M. Schwartz A. Zhiboedov 18 5 0 18 Aug 2023
A hybrid Decoder-DeepONet operator regression framework for unaligned observation data Bo Chen Chenyu Wang Weipeng Li Haiyang Fu 36 9 0 18 Aug 2023
Neural oscillators for generalization of physics-informed machine learning Taniya Kapoor Abhishek Chandra D. Tartakovsky Hongrui Wang Alfredo Núñez R. Dollevoet AI4CE 32 11 0 17 Aug 2023
Enhancing Convergence Speed with Feature-Enforcing Physics-Informed Neural Networks: Utilizing Boundary Conditions as Prior Knowledge for Faster Convergence Mahyar Jahaninasab M. A. Bijarchi 13 0 0 17 Aug 2023
GRINN: A Physics-Informed Neural Network for solving hydrodynamic systems in the presence of self-gravity Sayantan Auddy Ramit Dey N. Turner S. Basu PINN AI4CE 17 4 0 15 Aug 2023
Deep Neural Operator Driven Real Time Inference for Nuclear Systems to Enable Digital Twin Solutions Kazuma Kobayashi S. B. Alam AI4CE 15 13 0 15 Aug 2023
The Hard-Constraint PINNs for Interface Optimal Control Problems M. Lai Yongcun Song Xiaoming Yuan Hangrui Yue Tianyou Zeng PINN 24 2 0 13 Aug 2023
A practical PINN framework for multi-scale problems with multi-magnitude loss terms Y. Wang Yanzhong Yao Jiawei Guo Zhiming Gao AI4CE 11 21 0 13 Aug 2023
Size Lowerbounds for Deep Operator Networks Anirbit Mukherjee Amartya Roy AI4CE 30 3 0 11 Aug 2023
Towards true discovery of the differential equations A. Hvatov Roman V. Titov 22 0 0 09 Aug 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 12 0 08 Aug 2023
Neural Schrödinger Bridge with Sinkhorn Losses: Application to Data-driven Minimum Effort Control of Colloidal Self-assembly Iman Nodozi Charlie Yan Mira M. Khare A. Halder A. Mesbah 19 5 0 26 Jul 2023
Multi-stage Neural Networks: Function Approximator of Machine Precision Yongjian Wang Ching-Yao Lai 53 36 0 18 Jul 2023
Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression Zhen Zhang Zongren Zou E. Kuhl George Karniadakis 28 42 0 16 Jul 2023
Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks Inbar Seroussi Asaf Miron Zohar Ringel PINN 40 0 0 12 Jul 2023
A Deep Learning Framework for Solving Hyperbolic Partial Differential Equations: Part I Rajat Arora PINN AI4CE 27 1 0 09 Jul 2023
Temporal Difference Learning for High-Dimensional PIDEs with Jumps Liwei Lu Hailong Guo Xueqing Yang Yi Zhu AI4CE 23 6 0 06 Jul 2023
A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture Jonghyuk Baek Jiun-Shyan Chen 34 12 0 04 Jul 2023