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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
Qade: Solving Differential Equations on Quantum Annealers J. C. Criado M. Spannowsky 62 13 0 07 Apr 2022
Certified machine learning: A posteriori error estimation for physics-informed neural networks Birgit Hillebrecht B. Unger PINN 88 15 0 31 Mar 2022
NUNet: Deep Learning for Non-Uniform Super-Resolution of Turbulent Flows Octavi Obiols-Sales Abhinav Vishnu Nicholas Malaya Aparna Chandramowlishwaran AI4CE 64 5 0 26 Mar 2022
Applications of physics informed neural operators S. Rosofsky Hani Al Majed Eliu A. Huerta PINN AI4CE 56 41 0 23 Mar 2022
An Adaptive and Scalable ANN-based Model-Order-Reduction Method for Large-Scale TO Designs Renkai Tan Chaojun Qian Dan Xu Wenjing Ye AI4CE 40 2 0 20 Mar 2022
$Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations$ Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations Ling Guo Hao Wu Xiao-Jun Yu Tao Zhou PINN AI4CE 64 63 0 16 Mar 2022
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 156 203 0 14 Mar 2022
Multigrid-augmented deep learning preconditioners for the Helmholtz equation Yael Azulay Eran Treister AI4CE 76 31 0 14 Mar 2022
Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged Learning V. Churchill Steve Manns Zhen Chen D. Xiu AI4CE 74 11 0 07 Mar 2022
Neural Ordinary Differential Equations for Nonlinear System Identification Aowabin Rahman Ján Drgoňa Aaron Tuor J. Strube 107 22 0 28 Feb 2022
EINNs: Epidemiologically-informed Neural Networks Alexander Rodríguez Jiaming Cui Naren Ramakrishnan B. Adhikari B. Prakash 76 30 0 21 Feb 2022
Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions Lesley Tan Liang Chen 63 15 0 17 Feb 2022
MIONet: Learning multiple-input operators via tensor product Pengzhan Jin Shuai Meng Lu Lu 95 176 0 12 Feb 2022
Physics-informed neural networks for solving parametric magnetostatic problems Andrés Beltrán-Pulido Ilias Bilionis D. Aliprantis 83 37 0 08 Feb 2022
Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks Mitchell Daneker Zhen Zhang George Karniadakis Lu Lu CML 52 36 0 03 Feb 2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Mathilde Mougeot PINN AI4CE 128 32 0 31 Jan 2022
Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization G. Luca E. Silverstein 85 11 0 26 Jan 2022
Numerical Approximation of Partial Differential Equations by a Variable Projection Method with Artificial Neural Networks S. Dong Jielin Yang 71 18 0 24 Jan 2022
Heat Conduction Plate Layout Optimization using Physics-driven Convolutional Neural Networks Hao Ma Yang-Tian Sun M. Chiarelli 35 2 0 21 Jan 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Yaoyu Zhang FaML 92 74 0 19 Jan 2022
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 138 1,305 0 14 Jan 2022
PINNs for the Solution of the Hyperbolic Buckley-Leverett Problem with a Non-convex Flux Function W. Diab M. A. Kobaisi PINN 28 6 0 29 Dec 2021
Deep neural networks for solving forward and inverse problems of (2+1)-dimensional nonlinear wave equations with rational solitons Zijian Zhou Li Wang Zhenya Yan 131 1 0 28 Dec 2021
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations Keju Tang Xiaoliang Wan Chao Yang 77 116 0 28 Dec 2021
Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations Shen Wang M. Nikfar Joshua C. Agar Yaling Liu PINN DiffM AI4CE 47 3 0 13 Dec 2021
A Continuous-time Stochastic Gradient Descent Method for Continuous Data Kexin Jin J. Latz Chenguang Liu Carola-Bibiane Schönlieb 91 9 0 07 Dec 2021
A generic physics-informed neural network-based framework for reliability assessment of multi-state systems Taotao Zhou Xiaoge Zhang E. Droguett A. Mosleh AI4CE 125 33 0 01 Dec 2021
Neural network stochastic differential equation models with applications to financial data forecasting Luxuan Yang Ting Gao Yubin Lu Jinqiao Duan Tao Liu AI4TS 102 41 0 25 Nov 2021
Data-driven discoveries of Bäcklund transforms and soliton evolution equations via deep neural network learning schemes Zijian Zhou Li Wang Weifang Weng Zhenya Yan 70 19 0 18 Nov 2021
A research framework for writing differentiable PDE discretizations in JAX A. Stanziola Simon Arridge B. Cox B. Treeby 54 8 0 09 Nov 2021
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 135 430 0 06 Nov 2021
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 91 475 0 01 Nov 2021
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method P. Chiu Jian Cheng Wong C. Ooi M. Dao Yew-Soon Ong PINN 75 221 0 29 Oct 2021
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Rafael Bischof M. Kraus PINN AI4CE 117 99 0 19 Oct 2021
Study of Drug Assimilation in Human System using Physics Informed Neural Networks Kanupriya Goswami Arpana Sharma Madhu Pruthi Richa Gupta 57 11 0 08 Oct 2021
A composable autoencoder-based iterative algorithm for accelerating numerical simulations Rishikesh Ranade C. Hill Haiyang He Amir Maleki Norman Chang Jay Pathak AI4CE 71 6 0 07 Oct 2021
Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training E. Haghighat Daniel Amini R. Juanes PINN AI4CE 113 102 0 06 Oct 2021
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries Yi-Zhou Wang Jia Sun Wei Li Zaiyuan Lu Yinghua Liu 123 41 0 25 Sep 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 86 82 0 20 Sep 2021
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 86 64 0 15 Sep 2021
Learning Density Distribution of Reachable States for Autonomous Systems Yue Meng Dawei Sun Zeng Qiu Md Tawhid Bin Waez Chuchu Fan 115 19 0 14 Sep 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks Christian Moya Guang Lin AI4CE PINN 109 39 0 09 Sep 2021
AdjointNet: Constraining machine learning models with physics-based codes S. Karra B. Ahmmed M. Mudunuru AI4CE PINN OOD 66 4 0 08 Sep 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 125 649 0 02 Sep 2021
SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets Octavi Obiols-Sales Abhinav Vishnu Nicholas Malaya Aparna Chandramowlishwaran AI4CE 76 25 0 17 Aug 2021
An Extensible Benchmark Suite for Learning to Simulate Physical Systems Karl Otness Arvi Gjoka Joan Bruna Daniele Panozzo Benjamin Peherstorfer T. Schneider Denis Zorin 103 23 0 09 Aug 2021
Numerical Solution of Stiff ODEs with Physics-Informed RPNNs Evangelos Galaris Gianluca Fabiani Francesco Calabrò D. Serafino Constantinos Siettos 49 2 0 03 Aug 2021
Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings B. Bahmani WaiChing Sun PINN AI4CE 98 18 0 24 Jul 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 91 227 0 16 Jul 2021
Meta-learning PINN loss functions Apostolos F. Psaros Kenji Kawaguchi George Karniadakis PINN 95 106 0 12 Jul 2021