DGM: A deep learning algorithm for solving partial differential equations

24 August 2017

Papers citing "DGM: A deep learning algorithm for solving partial differential equations"

50 / 315 papers shown

Title
Solving Nonlinear PDEs with Sparse Radial Basis Function Networks Zihan Shao Konstantin Pieper Xiaochuan Tian 33 0 0 12 May 2025
Reverse-BSDE Monte Carlo Jairon H. N. Batista Flávio B. Gonçalves Yuri F. Saporito Rodrigo S. Targino DiffM 36 0 0 11 May 2025
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method Conor Rowan K. Maute Alireza Doostan AI4CE 53 0 0 08 May 2025
Error Analysis of Deep PDE Solvers for Option Pricing Jasper Rou 53 0 0 08 May 2025
Integration Matters for Learning PDEs with Backwards SDEs Sungje Park Stephen Tu PINN 65 0 0 02 May 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 83 0 0 25 Apr 2025
From Equations to Insights: Unraveling Symbolic Structures in PDEs with LLMs Rohan Bhatnagar Ling Liang Krish Patel Haizhao Yang 36 0 0 13 Mar 2025
Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble Zongren Zou Zhicheng Wang George Karniadakis PINN AI4CE 73 2 0 08 Mar 2025
Verification and Validation for Trustworthy Scientific Machine Learning John D. Jakeman Lorena A. Barba J. Martins Thomas O'Leary-Roseberry AI4CE 65 0 0 21 Feb 2025
Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations Yuan Chen Abdul Khaliq Khaled M. Furati AI4CE 66 0 0 20 Feb 2025
Machine learning for modelling unstructured grid data in computational physics: a review Sibo Cheng Marc Bocquet Weiping Ding Tobias S. Finn Rui Fu ... Yong Zeng Mingrui Zhang Hao Zhou Kewei Zhu Rossella Arcucci PINN AI4CE 119 0 0 13 Feb 2025
Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks A. Celaya Yimo Wang David T. Fuentes Beatrice Riviere 41 0 0 12 Feb 2025
DGNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling Yaohua Zang P. Koutsourelakis AI4CE 56 1 0 10 Feb 2025
Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths Yueyang Wang Kejun Tang Xili Wang Xiaoliang Wan Weiqing Ren Chao Yang 40 0 0 28 Jan 2025
ELM-DeepONets: Backpropagation-Free Training of Deep Operator Networks via Extreme Learning Machines Hwijae Son 56 0 0 17 Jan 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 82 1 0 15 Dec 2024
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Zekun Shi Zheyuan Hu Min Lin Kenji Kawaguchi 224 6 0 27 Nov 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 32 2 0 04 Oct 2024
Convergence Guarantees for Neural Network-Based Hamilton-Jacobi Reachability William Hofgard 31 2 0 03 Oct 2024
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups Zakhar Shumaylov Peter Zaika James Rowbottom Ferdia Sherry Melanie Weber Carola-Bibiane Schönlieb 54 2 0 03 Oct 2024
Model Comparisons: XNet Outperforms KAN Xin Li Zhihong Xia Xiaotao Zheng 47 0 0 02 Oct 2024
Cauchy activation function and XNet Xin Li Zhihong Xia Hongkun Zhang 53 4 0 28 Sep 2024
Harnessing physics-informed operators for high-dimensional reliability analysis problems N Navaneeth Tushar Souvik Chakraborty AI4CE 45 0 0 07 Sep 2024
Practical Aspects on Solving Differential Equations Using Deep Learning: A Primer Georgios Is. Detorakis 30 0 0 21 Aug 2024
Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs Hrishikesh Viswanath Yue Chang Julius Berner Julius Berner Peter Yichen Chen Aniket Bera AI4CE 68 2 0 04 Jul 2024
Efficient Shallow Ritz Method For 1D Diffusion-Reaction Problems Zhiqiang Cai Anastassia Doktorova Robert D. Falgout César Herrera 28 0 0 01 Jul 2024
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study Milad Ramezankhani A. Deodhar Rishi Parekh Dagnachew Birru AI4CE 50 3 0 20 Jun 2024
HDNet: Physics-Inspired Neural Network for Flow Estimation based on Helmholtz Decomposition Miao Qi R. Idoughi Wolfgang Heidrich PINN MDE 28 1 0 12 Jun 2024
Solving Poisson Equations using Neural Walk-on-Spheres Hong Chul Nam Julius Berner Anima Anandkumar 47 3 0 05 Jun 2024
Initialization-enhanced Physics-Informed Neural Network with Domain Decomposition (IDPINN) Chenhao Si Ming Yan AI4CE PINN 41 3 0 05 Jun 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 41 3 0 29 May 2024
Convergence of the Deep Galerkin Method for Mean Field Control Problems William Hofgard Jingruo Sun Asaf Cohen AI4CE 39 3 0 22 May 2024
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs Ariel Neufeld Philipp Schmocker Sizhou Wu 45 7 0 08 May 2024
A score-based particle method for homogeneous Landau equation Yan Huang Li Wang OT 60 5 0 08 May 2024
Macroscopic auxiliary asymptotic preserving neural networks for the linear radiative transfer equations Hongyan Li Song Jiang Wenjun Sun Liwei Xu Guanyu Zhou 45 2 0 04 Mar 2024
A time-stepping deep gradient flow method for option pricing in (rough) diffusion models A. Papapantoleon Jasper Rou 26 2 0 01 Mar 2024
Learning solution operators of PDEs defined on varying domains via MIONet Shanshan Xiao Pengzhan Jin Yifa Tang 55 3 0 23 Feb 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning Hao Liu Biraj Dahal Rongjie Lai Wenjing Liao AI4CE 39 5 0 19 Jan 2024
Approximation of Solution Operators for High-dimensional PDEs Nathan Gaby Xiaojing Ye 30 0 0 18 Jan 2024
A deep implicit-explicit minimizing movement method for option pricing in jump-diffusion models E. Georgoulis A. Papapantoleon Costas Smaragdakis 33 7 0 12 Jan 2024
Generating synthetic data for neural operators Erisa Hasani Rachel A. Ward AI4CE 70 8 0 04 Jan 2024
Physics Informed Neural Network for Option Pricing Ashish Dhiman Yibei Hu 16 3 0 10 Dec 2023
GIT-Net: Generalized Integral Transform for Operator Learning Chao Wang Alexandre H. Thiery AI4CE 37 0 0 05 Dec 2023
Adaptive importance sampling for Deep Ritz Xiaoliang Wan Tao Zhou Yuancheng Zhou 29 2 0 26 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 28 0 0 16 Oct 2023
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Latent assimilation with implicit neural representations for unknown dynamics Zhuoyuan Li Bin Dong Pingwen Zhang AI4CE 24 3 0 18 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
Solving multiscale elliptic problems by sparse radial basis function neural networks Zhiwen Wang Minxin Chen Jingrun Chen 57 15 0 01 Sep 2023
Predicting and explaining nonlinear material response using deep Physically Guided Neural Networks with Internal Variables Javier Orera-Echeverria J. Ayensa-Jiménez Manuel Doblaré 30 1 0 07 Aug 2023