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Trainability and Accuracy of Neural Networks: An Interacting Particle
  System Approach

Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

2 May 2018
Grant M. Rotskoff
Eric Vanden-Eijnden
ArXivPDFHTML

Papers citing "Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach"

16 / 16 papers shown
Title
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Francesco Camilli
D. Tieplova
Eleonora Bergamin
Jean Barbier
39
0
0
06 May 2025
Don't be lazy: CompleteP enables compute-efficient deep transformers
Don't be lazy: CompleteP enables compute-efficient deep transformers
Nolan Dey
Bin Claire Zhang
Lorenzo Noci
Mufan Bill Li
Blake Bordelon
Shane Bergsma
C. Pehlevan
Boris Hanin
Joel Hestness
37
0
0
02 May 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon
C. Pehlevan
AI4CE
59
1
0
04 Feb 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
Ziang Chen
Rong Ge
MLT
53
1
0
10 Jan 2025
Emergence of meta-stable clustering in mean-field transformer models
Emergence of meta-stable clustering in mean-field transformer models
Giuseppe Bruno
Federico Pasqualotto
Andrea Agazzi
42
6
0
30 Oct 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine Dominé
Nicolas Anguita
A. Proca
Lukas Braun
D. Kunin
P. Mediano
Andrew M. Saxe
30
3
0
22 Sep 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
29
2
0
30 May 2024
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Luca Arnaboldi
Yatin Dandi
Florent Krzakala
Luca Pesce
Ludovic Stephan
59
11
0
24 May 2024
High-dimensional scaling limits and fluctuations of online least-squares
  SGD with smooth covariance
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
Krishnakumar Balasubramanian
Promit Ghosal
Ye He
23
5
0
03 Apr 2023
Online Learning for the Random Feature Model in the Student-Teacher
  Framework
Online Learning for the Random Feature Model in the Student-Teacher Framework
Roman Worschech
B. Rosenow
28
0
0
24 Mar 2023
Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic
  Gradient Descent
Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent
Benjamin Gess
Sebastian Kassing
Vitalii Konarovskyi
DiffM
16
6
0
14 Feb 2023
Learning threshold neurons via the "edge of stability"
Learning threshold neurons via the "edge of stability"
Kwangjun Ahn
Sébastien Bubeck
Sinho Chewi
Y. Lee
Felipe Suarez
Yi Zhang
MLT
31
36
0
14 Dec 2022
Proximal Mean Field Learning in Shallow Neural Networks
Proximal Mean Field Learning in Shallow Neural Networks
Alexis M. H. Teter
Iman Nodozi
A. Halder
FedML
23
1
0
25 Oct 2022
A blob method for inhomogeneous diffusion with applications to
  multi-agent control and sampling
A blob method for inhomogeneous diffusion with applications to multi-agent control and sampling
Katy Craig
Karthik Elamvazhuthi
M. Haberland
O. Turanova
17
15
0
25 Feb 2022
Deep limits and cut-off phenomena for neural networks
Deep limits and cut-off phenomena for neural networks
B. Avelin
A. Karlsson
AI4CE
15
2
0
21 Apr 2021
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
175
1,182
0
30 Nov 2014
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