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"

21 / 21 papers shown

Title
Fractional-Boundary-Regularized Deep Galerkin Method for Variational Inequalities in Mixed Optimal Stopping and Control Yun Zhao Harry Zheng 11 0 0 25 May 2025
A brief review of the Deep BSDE method for solving high-dimensional partial differential equations Jiequn Han Arnulf Jentzen Weinan E AI4CE 38 0 0 07 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 97 0 0 25 Apr 2025
Verification and Validation for Trustworthy Scientific Machine Learning John D. Jakeman Lorena A. Barba J. Martins Thomas O'Leary-Roseberry AI4CE 76 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 112 0 0 20 Feb 2025
DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling Yaohua Zang P. Koutsourelakis AI4CE 74 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 56 0 0 28 Jan 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 93 1 0 15 Dec 2024
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Zekun Shi Zheyuan Hu Min Lin Kenji Kawaguchi 324 7 0 27 Nov 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 61 2 0 04 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 61 4 0 03 Oct 2024
Cauchy activation function and XNet Xin Li Zhihong Xia Hongkun Zhang 98 4 0 28 Sep 2024
Practical Aspects on Solving Differential Equations Using Deep Learning: A Primer Georgios Is. Detorakis 73 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 78 2 0 04 Jul 2024
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs Ariel Neufeld Philipp Schmocker Sizhou Wu 60 7 0 08 May 2024
A score-based particle method for homogeneous Landau equation Yan Huang Li Wang OT 72 5 0 08 May 2024
A time-stepping deep gradient flow method for option pricing in (rough) diffusion models A. Papapantoleon Jasper Rou 47 2 0 01 Mar 2024
A deep implicit-explicit minimizing movement method for option pricing in jump-diffusion models E. Georgoulis A. Papapantoleon Costas Smaragdakis 54 7 0 12 Jan 2024
Generating synthetic data for neural operators Erisa Hasani Rachel A. Ward AI4CE 87 8 0 04 Jan 2024
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee Mo Zhou Jian-Xiong Lu 58 8 0 11 Feb 2023
Deep Relaxation: partial differential equations for optimizing deep neural networks Pratik Chaudhari Adam M. Oberman Stanley Osher Stefano Soatto G. Carlier 120 153 0 17 Apr 2017