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Robust SDE-Based Variational Formulations for Solving Linear PDEs via
  Deep Learning

Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning

21 June 2022
Lorenz Richter
Julius Berner
ArXivPDFHTML

Papers citing "Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning"

13 / 13 papers shown
Title
Deep Generalized Schr\"odinger Bridges: From Image Generation to Solving Mean-Field Games
Deep Generalized Schr\"odinger Bridges: From Image Generation to Solving Mean-Field Games
Guan-Horng Liu
Tianrong Chen
Evangelos A. Theodorou
26
0
0
31 Dec 2024
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Byoungwoo Park
Hyungi Lee
Juho Lee
AI4TS
41
0
0
08 Oct 2024
Base Models for Parabolic Partial Differential Equations
Base Models for Parabolic Partial Differential Equations
Xingzi Xu
Ali Hasan
Jie Ding
Vahid Tarokh
45
1
0
17 Jul 2024
Dynamical Measure Transport and Neural PDE Solvers for Sampling
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
39
8
0
10 Jul 2024
Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs
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
63
2
0
04 Jul 2024
Solving Poisson Equations using Neural Walk-on-Spheres
Solving Poisson Equations using Neural Walk-on-Spheres
Hong Chul Nam
Julius Berner
Anima Anandkumar
37
3
0
05 Jun 2024
Neural Operators for Accelerating Scientific Simulations and Design
Neural Operators for Accelerating Scientific Simulations and Design
Kamyar Azzizadenesheli
Nikola B. Kovachki
Zong-Yi Li
Miguel Liu-Schiaffini
Jean Kossaifi
Anima Anandkumar
AI4CE
35
122
0
27 Sep 2023
From continuous-time formulations to discretization schemes: tensor
  trains and robust regression for BSDEs and parabolic PDEs
From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEs
Lorenz Richter
Leon Sallandt
Nikolas Nusken
19
4
0
28 Jul 2023
Improved sampling via learned diffusions
Improved sampling via learned diffusions
Lorenz Richter
Julius Berner
DiffM
34
52
0
03 Jul 2023
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
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
51
4
0
10 Feb 2023
An optimal control perspective on diffusion-based generative modeling
An optimal control perspective on diffusion-based generative modeling
Julius Berner
Lorenz Richter
Karen Ullrich
DiffM
28
80
0
02 Nov 2022
Learning ReLU networks to high uniform accuracy is intractable
Learning ReLU networks to high uniform accuracy is intractable
Julius Berner
Philipp Grohs
F. Voigtlaender
32
4
0
26 May 2022
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
Nikolas Nusken
Lorenz Richter
PINN
DiffM
31
27
0
07 Dec 2021
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