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Stochastic Optimal Control Matching
v1v2v3v4 (latest)

Stochastic Optimal Control Matching

4 December 2023
Carles Domingo-Enrich
Jiequn Han
Brandon Amos
Joan Bruna
Ricky T. Q. Chen
    DiffM
ArXiv (abs)PDFHTMLGithub (35★)

Papers citing "Stochastic Optimal Control Matching"

15 / 15 papers shown
Title
A brief review of the Deep BSDE method for solving high-dimensional partial differential equations
A brief review of the Deep BSDE method for solving high-dimensional partial differential equations
Jiequn Han
Arnulf Jentzen
Weinan E
AI4CE
63
1
0
07 May 2025
Stochastic Optimal Control for Diffusion Bridges in Function Spaces
Stochastic Optimal Control for Diffusion Bridges in Function Spaces
Byoungwoo Park
Jungwon Choi
Sungbin Lim
Juho Lee
117
3
0
31 May 2024
Improved sampling via learned diffusions
Improved sampling via learned diffusions
Lorenz Richter
Julius Berner
DiffM
99
64
0
03 Jul 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
133
95
0
02 Nov 2022
Path Integral Sampler: a stochastic control approach for sampling
Path Integral Sampler: a stochastic control approach for sampling
Qinsheng Zhang
Yongxin Chen
DiffM
100
118
0
30 Nov 2021
Score-Based Generative Modeling through Stochastic Differential
  Equations
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song
Jascha Narain Sohl-Dickstein
Diederik P. Kingma
Abhishek Kumar
Stefano Ermon
Ben Poole
DiffMSyDa
364
6,586
0
26 Nov 2020
Convergence Analysis of Machine Learning Algorithms for the Numerical
  Solution of Mean Field Control and Games: II -- The Finite Horizon Case
Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case
René Carmona
Mathieu Laurière
72
99
0
05 Aug 2019
Generative Modeling by Estimating Gradients of the Data Distribution
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
Stefano Ermon
SyDaDiffM
258
3,961
0
12 Jul 2019
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
446
5,168
0
19 Jun 2018
Deep Relaxation: partial differential equations for optimizing deep
  neural networks
Deep Relaxation: partial differential equations for optimizing deep neural networks
Pratik Chaudhari
Adam M. Oberman
Stanley Osher
Stefano Soatto
G. Carlier
150
154
0
17 Apr 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for
  Variational Inference
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Geoffrey Roeder
Yuhuai Wu
David Duvenaud
BDL
142
202
0
27 Mar 2017
Safe and Efficient Off-Policy Reinforcement Learning
Safe and Efficient Off-Policy Reinforcement Learning
Rémi Munos
T. Stepleton
Anna Harutyunyan
Marc G. Bellemare
OffRL
138
618
0
08 Jun 2016
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRLBDL
322
4,197
0
21 May 2015
Adaptive importance sampling for control and inference
Adaptive importance sampling for control and inference
H. Kappen
Hans Christian Ruiz
80
101
0
07 May 2015
Infinite-Horizon Policy-Gradient Estimation
Infinite-Horizon Policy-Gradient Estimation
Jonathan Baxter
Peter L. Bartlett
109
812
0
03 Jun 2011
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