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Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks

Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks

19 May 2019
Kaitong Hu
Zhenjie Ren
David Siska
Lukasz Szpruch
    MLT
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Papers citing "Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks"

21 / 21 papers shown
Title
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games
Yulong Lu
Pierre Monmarché
MLT
29
0
0
12 May 2025
Mirror Mean-Field Langevin Dynamics
Mirror Mean-Field Langevin Dynamics
Anming Gu
Juno Kim
31
0
0
05 May 2025
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime
Raphael Barboni
Gabriel Peyré
François-Xavier Vialard
MLT
34
0
0
25 Apr 2025
Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity
Shuailong Zhu
Xiaohui Chen
77
0
0
28 Jan 2025
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
Alireza Mousavi-Hosseini
Denny Wu
Murat A. Erdogdu
MLT
AI4CE
27
6
0
14 Aug 2024
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
Anming Gu
Edward Chien
Kristjan Greenewald
44
4
0
11 Jun 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View
Symmetries in Overparametrized Neural Networks: A Mean-Field View
Javier Maass Martínez
Joaquin Fontbona
FedML
MLT
38
2
0
30 May 2024
Mean-field underdamped Langevin dynamics and its spacetime
  discretization
Mean-field underdamped Langevin dynamics and its spacetime discretization
Qiang Fu
Ashia Wilson
34
4
0
26 Dec 2023
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation
Nawaf Bou-Rabee
Katharina Schuh
23
7
0
22 Aug 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
Ö. Deniz Akyildiz
F. R. Crucinio
Mark Girolami
Tim Johnston
Sotirios Sabanis
25
10
0
23 Mar 2023
Doubly Regularized Entropic Wasserstein Barycenters
Doubly Regularized Entropic Wasserstein Barycenters
Lénaïc Chizat
18
11
0
21 Mar 2023
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum
  Problems
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems
Atsushi Nitanda
Kazusato Oko
Denny Wu
Nobuhito Takenouchi
Taiji Suzuki
24
3
0
06 Mar 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
43
30
0
06 Dec 2022
Trajectory Inference via Mean-field Langevin in Path Space
Trajectory Inference via Mean-field Langevin in Path Space
Lénaïc Chizat
Stephen X. Zhang
Matthieu Heitz
Geoffrey Schiebinger
31
20
0
14 May 2022
Convex Analysis of the Mean Field Langevin Dynamics
Convex Analysis of the Mean Field Langevin Dynamics
Atsushi Nitanda
Denny Wu
Taiji Suzuki
MLT
59
64
0
25 Jan 2022
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural
  Network Approximation in the Mean-Field Regime
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime
B. Kerimkulov
J. Leahy
David Siska
Lukasz Szpruch
22
11
0
18 Jan 2022
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
A. Shevchenko
Vyacheslav Kungurtsev
Marco Mondelli
MLT
36
13
0
03 Nov 2021
Gradient Flows for Regularized Stochastic Control Problems
Gradient Flows for Regularized Stochastic Control Problems
David Siska
Lukasz Szpruch
8
20
0
10 Jun 2020
Can Shallow Neural Networks Beat the Curse of Dimensionality? A mean
  field training perspective
Can Shallow Neural Networks Beat the Curse of Dimensionality? A mean field training perspective
Stephan Wojtowytsch
E. Weinan
MLT
21
48
0
21 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
31
78
0
11 Mar 2020
Unbiased deep solvers for linear parametric PDEs
Unbiased deep solvers for linear parametric PDEs
Marc Sabate Vidales
David Siska
Lukasz Szpruch
OOD
24
7
0
11 Oct 2018
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