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
Achieving High Accuracy with PINNs via Energy Natural Gradients Johannes Müller Marius Zeinhofer 13 5 0 25 Feb 2023
Elliptic PDE learning is provably data-efficient N. Boullé Diana Halikias Alex Townsend 28 18 0 24 Feb 2023
h-analysis and data-parallel physics-informed neural networks Paul Escapil-Inchauspé G. A. Ruz PINN AI4CE 29 2 0 17 Feb 2023
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach Yongcun Song Xiaoming Yuan Hangrui Yue PINN 32 6 0 16 Feb 2023
On the Generalization of PINNs outside the training domain and the Hyperparameters influencing it Andrea Bonfanti Roberto Santana M. Ellero Babak Gholami AI4CE PINN 43 3 0 15 Feb 2023
Can Physics-Informed Neural Networks beat the Finite Element Method? T. G. Grossmann U. J. Komorowska J. Latz Carola-Bibiane Schönlieb PINN AI4CE 23 86 0 08 Feb 2023
Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation Zhi-Hao Gao Tao Tang Liang Yan Tao Zhou 37 18 0 03 Feb 2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry Jian Cheng Wong P. Chiu C. Ooi M. Dao Yew-Soon Ong AI4CE PINN 22 10 0 03 Feb 2023
Neural Control of Parametric Solutions for High-dimensional Evolution PDEs Nathan Gaby X. Ye Haomin Zhou 19 6 0 31 Jan 2023
TransNet: Transferable Neural Networks for Partial Differential Equations Zezhong Zhang F. Bao L. Ju Guannan Zhang 16 3 0 27 Jan 2023
Improved generalization with deep neural operators for engineering systems: Path towards digital twin Kazuma Kobayashi James Daniell S. B. Alam AI4CE 36 20 0 17 Jan 2023
BINN: A deep learning approach for computational mechanics problems based on boundary integral equations Jia Sun Yinghua Liu Yizheng Wang Z. Yao Xiao-ping Zheng PINN AI4CE 22 23 0 11 Jan 2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences Chaopeng Shen A. Appling Pierre Gentine Toshiyuki Bandai H. Gupta ... Chris Rackauckas Tirthankar Roy Chonggang Xu Binayak Mohanty K. Lawson AI4CE 42 14 0 10 Jan 2023
Investigations on convergence behaviour of Physics Informed Neural Networks across spectral ranges and derivative orders Mayank Deshpande Siddharth Agarwal V. Snigdha A. K. Bhattacharya 6 4 0 07 Jan 2023
MC-Nonlocal-PINNs: handling nonlocal operators in PINNs via Monte Carlo sampling Xiaodong Feng Yue Qian W. Shen 25 3 0 26 Dec 2022
Fixed-budget online adaptive learning for physics-informed neural networks. Towards parameterized problem inference T. Nguyen T. Dairay Raphael Meunier Christophe Millet Mathilde Mougeot OOD AI4CE 15 5 0 22 Dec 2022
Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media Salah A. Faroughi Ramin Soltanmohammad Pingki Datta S. K. Mahjour S. Faroughi 21 22 0 17 Dec 2022
Reliable extrapolation of deep neural operators informed by physics or sparse observations Min Zhu Handi Zhang Anran Jiao George Karniadakis Lu Lu 50 91 0 13 Dec 2022
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 23 34 0 06 Dec 2022
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints Kaustubh Sridhar Souradeep Dutta James Weimer Insup Lee 30 7 0 02 Dec 2022
On the Compatibility between Neural Networks and Partial Differential Equations for Physics-informed Learning Kuangdai Leng Jeyan Thiyagalingam PINN 26 3 0 01 Dec 2022
VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations Bin Shan Ye Li Sheng-Jun Huang PINN 29 2 0 30 Nov 2022
Accelerated Solutions of Coupled Phase-Field Problems using Generative Adversarial Networks Vir Karan A. M. Indresh S. Bhattacharyya AI4CE 14 0 0 22 Nov 2022
Convergence analysis of unsupervised Legendre-Galerkin neural networks for linear second-order elliptic PDEs Seungchan Ko S. Yun Youngjoon Hong 22 5 0 16 Nov 2022
Physics-informed neural networks for operator equations with stochastic data Paul Escapil-Inchauspé G. A. Ruz 34 2 0 15 Nov 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics Esha Saha L. Ho Giang Tran 36 5 0 11 Nov 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 29 18 0 27 Oct 2022
A Novel Adaptive Causal Sampling Method for Physics-Informed Neural Networks Jia Guo Haifeng Wang Chenping Hou 13 7 0 24 Oct 2022
Less Emphasis on Difficult Layer Regions: Curriculum Learning for Singularly Perturbed Convection-Diffusion-Reaction Problems Yufeng Wang Cong Xu Min Yang Jin Zhang 11 4 0 23 Oct 2022
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks Shibo Li Michael Penwarden Yiming Xu Conor Tillinghast Akil Narayan Robert M. Kirby Shandian Zhe AI4CE 21 4 0 23 Oct 2022
A Dimension-Augmented Physics-Informed Neural Network (DaPINN) with High Level Accuracy and Efficiency Weilong Guan Kai-Ping Yang Yinsheng Chen Zhong Guan PINN AI4CE 18 12 0 19 Oct 2022
Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks Wei Peng Wenjuan Yao Weien Zhou Xiaoya Zhang Weijie Yao PINN 56 5 0 19 Oct 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 20 4 0 14 Oct 2022
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning M. Takamoto T. Praditia Raphael Leiteritz Dan MacKinlay Francesco Alesiani Dirk Pflüger Mathias Niepert AI4CE 30 209 0 13 Oct 2022
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade C. Hill Lalit Ghule Jay Pathak AI4CE 33 7 0 11 Oct 2022
A Method for Computing Inverse Parametric PDE Problems with Random-Weight Neural Networks S. Dong Yiran Wang 29 20 0 09 Oct 2022
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs Songming Liu Zhongkai Hao Chengyang Ying Hang Su Jun Zhu Ze Cheng AI4CE 18 17 0 06 Oct 2022
Optimization-Informed Neural Networks Da-Lin Wu A. Lisser 27 0 0 05 Oct 2022
NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning Buyun Liang Tim Mitchell Ju Sun OOD 18 7 0 03 Oct 2022
High Precision Differentiation Techniques for Data-Driven Solution of Nonlinear PDEs by Physics-Informed Neural Networks M. Mukhametzhanov 18 0 0 02 Oct 2022
Failure-informed adaptive sampling for PINNs Zhiwei Gao Liang Yan Tao Zhou 18 79 0 01 Oct 2022
Implicit Neural Spatial Representations for Time-dependent PDEs Honglin Chen Rundi Wu E. Grinspun Changxi Zheng Julius Berner AI4CE 25 33 0 30 Sep 2022
On Physics-Informed Neural Networks for Quantum Computers Stefano Markidis PINN 32 18 0 28 Sep 2022
Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time series J. Vilar L. Saiz 22 6 0 16 Sep 2022
MRF-PINN: A Multi-Receptive-Field convolutional physics-informed neural network for solving partial differential equations Shihong Zhang Chi Zhang Bo Wang AI4CE 24 3 0 06 Sep 2022
$Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator$ Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator Ming Zhong Zhenya Yan 19 14 0 29 Aug 2022
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies Adam Thelen Xiaoge Zhang Olga Fink Yan Lu Sayan Ghosh B. Youn Michael D. Todd S. Mahadevan Chao Hu Zhen Hu SyDa AI4CE 27 188 0 26 Aug 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 32 37 0 25 Aug 2022
A Physics-informed Deep Learning Approach for Minimum Effort Stochastic Control of Colloidal Self-Assembly Iman Nodozi Jared O’Leary A. Mesbah A. Halder 11 11 0 19 Aug 2022