Interpolating between BSDEs and PINNs: deep learning for elliptic and
parabolic boundary value problems

Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems

7 December 2021

Papers citing "Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems"

17 / 17 papers shown

Title
Integration Matters for Learning PDEs with Backwards SDEs Sungje Park Stephen Tu PINN 40 0 0 02 May 2025
Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths Yueyang Wang Kejun Tang Xili Wang Xiaoliang Wan Weiqing Ren Chao Yang 32 0 0 28 Jan 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner Lorenz Richter Marcin Sendera Jarrid Rector-Brooks Nikolay Malkin OffRL 44 3 0 10 Jan 2025
Dynamical Measure Transport and Neural PDE Solvers for Sampling Jingtong Sun Julius Berner Lorenz Richter Marius Zeinhofer Johannes Müller Kamyar Azizzadenesheli Anima Anandkumar OT DiffM 21 8 0 10 Jul 2024
Solving Poisson Equations using Neural Walk-on-Spheres Hong Chul Nam Julius Berner Anima Anandkumar 17 3 0 05 Jun 2024
Control, Transport and Sampling: Towards Better Loss Design Qijia Jiang David Nabergoj OT 22 0 0 22 May 2024
From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs Lorenz Richter Leon Sallandt Nikolas Nusken 9 4 0 28 Jul 2023
Transport meets Variational Inference: Controlled Monte Carlo Diffusions Francisco Vargas Shreyas Padhy Denis Blessing Nikolas Nusken DiffM OT 21 3 0 03 Jul 2023
Deep Stochastic Mechanics Elena Orlova Aleksei Ustimenko Ruoxi Jiang Peter Y. Lu Rebecca Willett DiffM 20 0 0 31 May 2023
Score Operator Newton transport N. Chandramoorthy F. Schaefer Youssef Marzouk OT 12 1 0 16 May 2023
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation Rui Zhang Qi Meng Rongchan Zhu Yue Wang Wenlei Shi Shihua Zhang Zhi-Ming Ma Tie-Yan Liu DiffM AI4CE 40 4 0 10 Feb 2023
An optimal control perspective on diffusion-based generative modeling Julius Berner Lorenz Richter Karen Ullrich DiffM 15 78 0 02 Nov 2022
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning Lorenz Richter Julius Berner 14 15 0 21 Jun 2022
A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems Jianfeng Lu Yulong Lu 21 27 0 04 May 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sifan Wang Hanwen Wang P. Perdikaris 126 435 0 18 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 197 2,254 0 18 Oct 2020
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 133 444 0 16 Sep 2019