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A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer
  Neural Networks

A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks

28 October 2022
Zhengdao Chen
Eric Vanden-Eijnden
Joan Bruna
    MLT
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Papers citing "A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks"

7 / 7 papers shown
Title
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space
Zhengdao Chen
28
1
0
03 Jul 2023
A Rainbow in Deep Network Black Boxes
A Rainbow in Deep Network Black Boxes
Florentin Guth
Brice Ménard
G. Rochette
S. Mallat
17
10
0
29 May 2023
On the Effect of Initialization: The Scaling Path of 2-Layer Neural
  Networks
On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks
Sebastian Neumayer
Lénaïc Chizat
M. Unser
25
2
0
31 Mar 2023
Mean-field analysis for heavy ball methods: Dropout-stability,
  connectivity, and global convergence
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence
Diyuan Wu
Vyacheslav Kungurtsev
Marco Mondelli
15
3
0
13 Oct 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
Optimization-Based Separations for Neural Networks
Optimization-Based Separations for Neural Networks
Itay Safran
Jason D. Lee
123
14
0
04 Dec 2021
Trainability and Accuracy of Neural Networks: An Interacting Particle
  System Approach
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach
Grant M. Rotskoff
Eric Vanden-Eijnden
59
118
0
02 May 2018
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