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A Mean-Field Optimal Control Formulation of Deep Learning

A Mean-Field Optimal Control Formulation of Deep Learning

3 July 2018
Weinan E
Jiequn Han
Qianxiao Li
    OOD
ArXivPDFHTML

Papers citing "A Mean-Field Optimal Control Formulation of Deep Learning"

35 / 35 papers shown
Title
Universal Approximation Theorem for Deep Q-Learning via FBSDE System
Universal Approximation Theorem for Deep Q-Learning via FBSDE System
Qian Qi
29
0
0
09 May 2025
Universal Approximation Theorem of Deep Q-Networks
Universal Approximation Theorem of Deep Q-Networks
Qian Qi
37
1
0
04 May 2025
Data Selection via Optimal Control for Language Models
Data Selection via Optimal Control for Language Models
Yuxian Gu
Li Dong
Hongning Wang
Y. Hao
Qingxiu Dong
Furu Wei
Minlie Huang
AI4CE
55
5
0
09 Oct 2024
Online Control-Informed Learning
Online Control-Informed Learning
Zihao Liang
Tianyu Zhou
Zehui Lu
Shaoshuai Mou
33
1
0
04 Oct 2024
Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size
Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size
Huafu Liao
Alpár R. Mészáros
Chenchen Mou
Chao Zhou
26
2
0
08 Apr 2024
Rethinking the Relationship between Recurrent and Non-Recurrent Neural
  Networks: A Study in Sparsity
Rethinking the Relationship between Recurrent and Non-Recurrent Neural Networks: A Study in Sparsity
Quincy Hershey
Randy Paffenroth
Harsh Nilesh Pathak
Simon Tavener
68
1
0
01 Apr 2024
The emergence of clusters in self-attention dynamics
The emergence of clusters in self-attention dynamics
Borjan Geshkovski
Cyril Letrouit
Yury Polyanskiy
Philippe Rigollet
22
46
0
09 May 2023
Neural Delay Differential Equations: System Reconstruction and Image
  Classification
Neural Delay Differential Equations: System Reconstruction and Image Classification
Qunxi Zhu
Yao Guo
Wei Lin
22
31
0
11 Apr 2023
Efficient Quantum Algorithms for Quantum Optimal Control
Efficient Quantum Algorithms for Quantum Optimal Control
Xiantao Li
Cong Wang
29
6
0
05 Apr 2023
Asymptotic Analysis of Deep Residual Networks
Asymptotic Analysis of Deep Residual Networks
R. Cont
Alain Rossier
Renyuan Xu
27
4
0
15 Dec 2022
Deep Generalized Schrödinger Bridge
Deep Generalized Schrödinger Bridge
Guan-Horng Liu
T. Chen
Oswin So
Evangelos A. Theodorou
OT
AI4CE
16
35
0
20 Sep 2022
The Mori-Zwanzig formulation of deep learning
The Mori-Zwanzig formulation of deep learning
D. Venturi
Xiantao Li
25
1
0
12 Sep 2022
Scaling ResNets in the Large-depth Regime
Scaling ResNets in the Large-depth Regime
P. Marion
Adeline Fermanian
Gérard Biau
Jean-Philippe Vert
26
16
0
14 Jun 2022
Why Quantization Improves Generalization: NTK of Binary Weight Neural
  Networks
Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks
Kaiqi Zhang
Ming Yin
Yu-Xiang Wang
MQ
24
4
0
13 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential
  Equations?
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?
Michael E. Sander
Pierre Ablin
Gabriel Peyré
35
25
0
29 May 2022
Physical Derivatives: Computing policy gradients by physical
  forward-propagation
Physical Derivatives: Computing policy gradients by physical forward-propagation
Arash Mehrjou
Ashkan Soleymani
Stefan Bauer
Bernhard Schölkopf
38
0
0
15 Jan 2022
Sinkformers: Transformers with Doubly Stochastic Attention
Sinkformers: Transformers with Doubly Stochastic Attention
Michael E. Sander
Pierre Ablin
Mathieu Blondel
Gabriel Peyré
29
76
0
22 Oct 2021
On the regularized risk of distributionally robust learning over deep
  neural networks
On the regularized risk of distributionally robust learning over deep neural networks
Camilo A. Garcia Trillos
Nicolas García Trillos
OOD
45
10
0
13 Sep 2021
Approximation capabilities of measure-preserving neural networks
Approximation capabilities of measure-preserving neural networks
Aiqing Zhu
Pengzhan Jin
Yifa Tang
26
8
0
21 Jun 2021
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint
M. Geist
Julien Pérolat
Mathieu Laurière
Romuald Elie
Sarah Perrin
Olivier Bachem
Rémi Munos
Olivier Pietquin
37
62
0
07 Jun 2021
Scaling Properties of Deep Residual Networks
Scaling Properties of Deep Residual Networks
A. Cohen
R. Cont
Alain Rossier
Renyuan Xu
25
18
0
25 May 2021
Neural network architectures using min-plus algebra for solving certain
  high dimensional optimal control problems and Hamilton-Jacobi PDEs
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs
Jérome Darbon
P. Dower
Tingwei Meng
8
22
0
07 May 2021
Momentum Residual Neural Networks
Momentum Residual Neural Networks
Michael E. Sander
Pierre Ablin
Mathieu Blondel
Gabriel Peyré
27
57
0
15 Feb 2021
Bayesian Uncertainty Estimation of Learned Variational MRI
  Reconstruction
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction
Dominik Narnhofer
Alexander Effland
Erich Kobler
Kerstin Hammernik
Florian Knoll
Thomas Pock
UQCV
BDL
23
49
0
12 Feb 2021
A Differential Game Theoretic Neural Optimizer for Training Residual
  Networks
A Differential Game Theoretic Neural Optimizer for Training Residual Networks
Guan-Horng Liu
T. Chen
Evangelos A. Theodorou
24
2
0
17 Jul 2020
Total Deep Variation: A Stable Regularizer for Inverse Problems
Total Deep Variation: A Stable Regularizer for Inverse Problems
Erich Kobler
Alexander Effland
K. Kunisch
Thomas Pock
MedIm
27
19
0
15 Jun 2020
Machine Learning and Control Theory
Machine Learning and Control Theory
A. Bensoussan
Yiqun Li
Dinh Phan Cao Nguyen
M. Tran
S. Yam
Xiang Zhou
AI4CE
32
12
0
10 Jun 2020
Robust Deep Learning as Optimal Control: Insights and Convergence
  Guarantees
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees
Jacob H. Seidman
Mahyar Fazlyab
V. Preciado
George J. Pappas
AAML
16
15
0
01 May 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable
  Optimization Via Overparameterization From Depth
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth
Yiping Lu
Chao Ma
Yulong Lu
Jianfeng Lu
Lexing Ying
MLT
39
78
0
11 Mar 2020
Machine Learning from a Continuous Viewpoint
Machine Learning from a Continuous Viewpoint
E. Weinan
Chao Ma
Lei Wu
27
102
0
30 Dec 2019
Deep Learning via Dynamical Systems: An Approximation Perspective
Deep Learning via Dynamical Systems: An Approximation Perspective
Qianxiao Li
Ting Lin
Zuowei Shen
AI4TS
AI4CE
22
107
0
22 Dec 2019
Neural Dynamics on Complex Networks
Neural Dynamics on Complex Networks
Chengxi Zang
Fei Wang
AI4CE
35
68
0
18 Aug 2019
Neural ODEs as the Deep Limit of ResNets with constant weights
Neural ODEs as the Deep Limit of ResNets with constant weights
B. Avelin
K. Nystrom
ODL
40
31
0
28 Jun 2019
A Review on Deep Learning in Medical Image Reconstruction
A Review on Deep Learning in Medical Image Reconstruction
Hai-Miao Zhang
Bin Dong
MedIm
35
122
0
23 Jun 2019
Data driven approximation of parametrized PDEs by Reduced Basis and
  Neural Networks
Data driven approximation of parametrized PDEs by Reduced Basis and Neural Networks
N. D. Santo
S. Deparis
Luca Pegolotti
19
66
0
02 Apr 2019
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