ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2404.05185
  4. Cited By
Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size
v1v2v3 (latest)

Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size

8 April 2024
Huafu Liao
Alpár R. Mészáros
Chenchen Mou
Chao Zhou
ArXiv (abs)PDFHTML

Papers citing "Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size"

23 / 23 papers shown
Title
Deep Learning for Mean Field Optimal Transport
Deep Learning for Mean Field Optimal Transport
Sebastian Baudelet
Brieuc Frénais
Mathieu Laurière
Amal Machtalay
Yuchen Zhu
OT
55
2
0
28 Feb 2023
Uniform-in-time propagation of chaos for mean field Langevin dynamics
Uniform-in-time propagation of chaos for mean field Langevin dynamics
Fan Chen
Zhenjie Ren
Song-bo Wang
89
31
0
06 Dec 2022
Deep Learning for Mean Field Games and Mean Field Control with
  Applications to Finance
Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
René Carmona
Mathieu Laurière
AI4CE
66
28
0
09 Jul 2021
Scaling Properties of Deep Residual Networks
Scaling Properties of Deep Residual Networks
A. Cohen
R. Cont
Alain Rossier
Renyuan Xu
51
19
0
25 May 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Zuowei Shen
Haizhao Yang
Shijun Zhang
171
118
0
28 Feb 2021
Neural Network Approximation: Three Hidden Layers Are Enough
Neural Network Approximation: Three Hidden Layers Are Enough
Zuowei Shen
Haizhao Yang
Shijun Zhang
82
120
0
25 Oct 2020
Deep Learning via Dynamical Systems: An Approximation Perspective
Deep Learning via Dynamical Systems: An Approximation Perspective
Qianxiao Li
Ting Lin
Zuowei Shen
AI4TSAI4CE
78
109
0
22 Dec 2019
Mean-Field Neural ODEs via Relaxed Optimal Control
Mean-Field Neural ODEs via Relaxed Optimal Control
Jean-François Jabir
D. vSivska
Lukasz Szpruch
MLT
99
38
0
11 Dec 2019
A Machine Learning Framework for Solving High-Dimensional Mean Field
  Game and Mean Field Control Problems
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Lars Ruthotto
Stanley Osher
Wuchen Li
L. Nurbekyan
Samy Wu Fung
AI4CE
122
220
0
04 Dec 2019
On the Convergence of Model Free Learning in Mean Field Games
On the Convergence of Model Free Learning in Mean Field Games
Romuald Elie
Julien Pérolat
Mathieu Laurière
Matthieu Geist
Olivier Pietquin
80
93
0
04 Jul 2019
Deep neural networks algorithms for stochastic control problems on
  finite horizon: numerical applications
Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications
Achref Bachouch
Côme Huré
N. Langrené
H. Pham
89
87
0
13 Dec 2018
Deep neural networks algorithms for stochastic control problems on
  finite horizon: convergence analysis
Deep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis
Côme Huré
H. Pham
Achref Bachouch
N. Langrené
55
67
0
11 Dec 2018
A Priori Estimates of the Population Risk for Two-layer Neural Networks
A Priori Estimates of the Population Risk for Two-layer Neural Networks
Weinan E
Chao Ma
Lei Wu
65
132
0
15 Oct 2018
A Mean-Field Optimal Control Formulation of Deep Learning
A Mean-Field Optimal Control Formulation of Deep Learning
Weinan E
Jiequn Han
Qianxiao Li
OOD
108
187
0
03 Jul 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
443
5,168
0
19 Jun 2018
On the Global Convergence of Gradient Descent for Over-parameterized
  Models using Optimal Transport
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat
Francis R. Bach
OT
214
737
0
24 May 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks
A Mean Field View of the Landscape of Two-Layers Neural Networks
Song Mei
Andrea Montanari
Phan-Minh Nguyen
MLT
105
862
0
18 Apr 2018
Maximum Principle Based Algorithms for Deep Learning
Maximum Principle Based Algorithms for Deep Learning
Qianxiao Li
Long Chen
Cheng Tai
E. Weinan
103
224
0
26 Oct 2017
Deep learning-based numerical methods for high-dimensional parabolic
  partial differential equations and backward stochastic differential equations
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
Weinan E
Jiequn Han
Arnulf Jentzen
125
797
0
15 Jun 2017
Stable Architectures for Deep Neural Networks
Stable Architectures for Deep Neural Networks
E. Haber
Lars Ruthotto
152
735
0
09 May 2017
EM Algorithm and Stochastic Control in Economics
EM Algorithm and Stochastic Control in Economics
S. Kou
X. Peng
Xingbo Xu
42
5
0
06 Nov 2016
Deep Learning Approximation for Stochastic Control Problems
Deep Learning Approximation for Stochastic Control Problems
Jiequn Han
E. Weinan
BDL
61
197
0
02 Nov 2016
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
467
43,347
0
11 Feb 2015
1