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
Worth of knowledge in deep learning Hao Xu Yuntian Chen Dong-juan Zhang 18 0 0 03 Jul 2023
Residual-based attention and connection to information bottleneck theory in PINNs Sokratis J. Anagnostopoulos Juan Diego Toscano Nikos Stergiopulos George Karniadakis 25 20 0 01 Jul 2023
Accelerated primal-dual methods with enlarged step sizes and operator learning for nonsmooth optimal control problems Yongcun Song Xiaoming Yuan Hangrui Yue AI4CE 19 2 0 01 Jul 2023
Machine learning for advancing low-temperature plasma modeling and simulation J. Trieschmann Luca Vialetto T. Gergs AI4CE 24 4 0 30 Jun 2023
Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation using Compact Implicit Layers Bar Lerer Ido Ben-Yair Eran Treister AI4CE 21 3 0 30 Jun 2023
Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery M. Maslyaev A. Hvatov 9 0 0 29 Jun 2023
Sampling weights of deep neural networks Erik Lien Bolager Iryna Burak Chinmay Datar Q. Sun Felix Dietrich BDL UQCV 19 16 0 29 Jun 2023
Separable Physics-Informed Neural Networks Junwoo Cho Seungtae Nam Hyunmo Yang S. Yun Youngjoon Hong Eunbyung Park PINN AI4CE 17 43 0 28 Jun 2023
Capturing the Diffusive Behavior of the Multiscale Linear Transport Equations by Asymptotic-Preserving Convolutional DeepONets Keke Wu Xiongbin Yan Shi Jin Zheng Ma 33 6 0 28 Jun 2023
Coupling parameter and particle dynamics for adaptive sampling in Neural Galerkin schemes Yuxiao Wen Eric Vanden-Eijnden Benjamin Peherstorfer 24 13 0 27 Jun 2023
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning Pu Ren N. Benjamin Erichson Shashank Subramanian Omer San Z. Lukić Michael W. Mahoney Michael W. Mahoney 47 13 0 24 Jun 2023
PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator Shaowu Pan E. Kaiser Brian M. de Silva J. Nathan Kutz Steven L. Brunton 21 8 0 22 Jun 2023
ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhoui Jie Liu PINN DiffM AI4CE 27 10 0 15 Jun 2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao J. Yao Chang Su Hang Su Ziao Wang ... Zeyu Xia Yichi Zhang Songming Liu Lu Lu Jun Zhu PINN 29 30 0 15 Jun 2023
Efficient Training of Physics-Informed Neural Networks with Direct Grid Refinement Algorithm Shikhar Nilabh F. Grandia 44 1 0 14 Jun 2023
Towards a Machine-Learned Poisson Solver for Low-Temperature Plasma Simulations in Complex Geometries Ihda Chaerony Siffa M. Becker K. Weltmann J. Trieschmann 38 2 0 13 Jun 2023
RANS-PINN based Simulation Surrogates for Predicting Turbulent Flows Shinjan Ghosh Amit Chakraborty Georgia Olympia Brikis Biswadip Dey PINN AI4CE 14 5 0 09 Jun 2023
Group Equivariant Fourier Neural Operators for Partial Differential Equations Jacob Helwig Xuan Zhang Cong Fu Jerry Kurtin Stephan Wojtowytsch Shuiwang Ji AI4CE 58 28 0 09 Jun 2023
MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks J. Yao Chang Su Zhongkai Hao Songming Liu Hang Su Jun Zhu ODL PINN AI4CE 11 12 0 05 Jun 2023
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs Keju Tang Jiayu Zhai Xiaoliang Wan Chao Yang 34 8 0 30 May 2023
Scalable Transformer for PDE Surrogate Modeling Zijie Li Dule Shu A. Farimani 35 67 0 27 May 2023
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations Yaohua Zang Gang Bao 32 4 0 21 May 2023
SHoP: A Deep Learning Framework for Solving High-order Partial Differential Equations Tingxiong Xiao Runzhao Yang Yuxiao Cheng J. Suo Qionghai Dai AI4CE 16 3 0 17 May 2023
Physics-Informed Neural Networks for Discovering Localised Eigenstates in Disordered Media Liam Harcombe Quanling Deng 29 6 0 11 May 2023
A Generalizable Physics-informed Learning Framework for Risk Probability Estimation Zhuoyuan Wang Yorie Nakahira OOD 11 5 0 10 May 2023
Physics-informed neural network for seismic wave inversion in layered semi-infinite domain Pu Ren Chengping Rao Haoqin Sun Yang Liu PINN 27 5 0 09 May 2023
Deep Learning for Solving and Estimating Dynamic Macro-Finance Models Benjamin Fan Edward Qiao Anran Jiao Zhouzhou Gu Wenhao Li Lu Lu 19 12 0 05 May 2023
Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell Bioreactors Tianqi Cui Tom S. Bertalan Nelson Ndahiro Pratik Khare Michael Betenbaugh C. Maranas Ioannis G. Kevrekidis 11 7 0 05 May 2023
Importance of equivariant and invariant symmetries for fluid flow modeling Varun Shankar Shivam Barwey Zico Kolter R. Maulik V. Viswanathan AI4CE 29 4 0 03 May 2023
MINN: Learning the dynamics of differential-algebraic equations and application to battery modeling Yicun Huang Changfu Zou Yong Li T. Wik PINN 31 10 0 27 Apr 2023
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks Hyeonjung Jung Jung Jayant Gupta B. Jayaprakash Matthew J. Eagon Harish Selvam Carl Molnar W. Northrop Shashi Shekhar AI4CE 35 5 0 26 Apr 2023
A mean-field games laboratory for generative modeling Benjamin J. Zhang M. Katsoulakis 30 18 0 26 Apr 2023
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems Xiaofei Guan Xintong Wang Hao Wu Zihao Yang Peng Yu PINN 27 11 0 25 Apr 2023
Estimating Failure Probability with Neural Operator Hybrid Approach Mujing Li Yani Feng Guanjie Wang 6 2 0 24 Apr 2023
HomPINNs: homotopy physics-informed neural networks for solving the inverse problems of nonlinear differential equations with multiple solutions Haoyang Zheng Yao Huang Ziyang Huang Wenrui Hao Guang Lin PINN 17 12 0 06 Apr 2023
$Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion$ Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion Xiongbin Yan Zhi-Qin John Xu Zheng Ma 32 2 0 03 Apr 2023
Optimal Mass Transport over the Euler Equation Charlie Yan Iman Nodozi A. Halder OT 20 1 0 02 Apr 2023
Multilevel CNNs for Parametric PDEs Cosmas Heiß Ingo Gühring Martin Eigel AI4CE 25 8 0 01 Apr 2023
Deep neural operator for learning transient response of interpenetrating phase composites subject to dynamic loading Minglei Lu Ali Mohammadi Zhaoxu Meng Xuhui Meng Gang Li Zhen Li AI4CE 13 12 0 30 Mar 2023
GAS: A Gaussian Mixture Distribution-Based Adaptive Sampling Method for PINNs Yuling Jiao Dingwei Li Xiliang Lu J. Yang Cheng Yuan 34 9 0 28 Mar 2023
Error Analysis of Physics-Informed Neural Networks for Approximating Dynamic PDEs of Second Order in Time Y. Qian Yongchao Zhang Yuanfei Huang S. Dong PINN 21 1 0 22 Mar 2023
ViTO: Vision Transformer-Operator O. Ovadia Adar Kahana P. Stinis Eli Turkel George Karniadakis 16 20 0 15 Mar 2023
Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review Hanxun Jin Enrui Zhang H. Espinosa AI4CE 28 68 0 14 Mar 2023
Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion Andrew Pensoneault Xueyu Zhu PINN 32 5 0 13 Mar 2023
Neural Partial Differential Equations with Functional Convolution Z. Wu Xingzhe He Yijun Li Cheng Yang Rui Liu S. Xiong Bo Zhu 23 1 0 10 Mar 2023
CoolPINNs: A Physics-informed Neural Network Modeling of Active Cooling in Vascular Systems N. V. Jagtap M. Mudunuru K. Nakshatrala PINN AI4CE 11 9 0 09 Mar 2023
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration Zhongyi Jiang Min Zhu Dongzhuo Li Qiuzi Li Yanhua O. Yuan Lu Lu AI4CE 46 50 0 08 Mar 2023
Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks Ye Li Songcan Chen Shengyi Huang PINN 20 3 0 03 Mar 2023
Active Learning and Bayesian Optimization: a Unified Perspective to Learn with a Goal Francesco Di Fiore Michela Nardelli L. Mainini 37 22 0 02 Mar 2023
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions Michael Penwarden Ameya Dilip Jagtap Shandian Zhe George Karniadakis Robert M. Kirby PINN AI4CE 23 57 0 28 Feb 2023