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The Gaussian equivalence of generative models for learning with shallow
  neural networks

The Gaussian equivalence of generative models for learning with shallow neural networks

25 June 2020
Sebastian Goldt
Bruno Loureiro
Galen Reeves
Florent Krzakala
M. Mézard
Lenka Zdeborová
    BDL
ArXivPDFHTML

Papers citing "The Gaussian equivalence of generative models for learning with shallow neural networks"

11 / 11 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
82
0
0
06 May 2025
auto-fpt: Automating Free Probability Theory Calculations for Machine Learning Theory
auto-fpt: Automating Free Probability Theory Calculations for Machine Learning Theory
Arjun Subramonian
Elvis Dohmatob
19
0
0
14 Apr 2025
Exact threshold for approximate ellipsoid fitting of random points
Exact threshold for approximate ellipsoid fitting of random points
Antoine Maillard
Afonso S. Bandeira
27
1
0
09 Oct 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models
David X. Wu
A. Sahai
21
2
0
23 Jun 2023
Precise Asymptotic Analysis of Deep Random Feature Models
Precise Asymptotic Analysis of Deep Random Feature Models
David Bosch
Ashkan Panahi
B. Hassibi
27
19
0
13 Feb 2023
Disentangling representations in Restricted Boltzmann Machines without
  adversaries
Disentangling representations in Restricted Boltzmann Machines without adversaries
Jorge Fernandez-de-Cossio-Diaz
Simona Cocco
R. Monasson
DRL
24
13
0
23 Jun 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step
  Improves the Representation
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Jimmy Ba
Murat A. Erdogdu
Taiji Suzuki
Zhichao Wang
Denny Wu
Greg Yang
MLT
27
121
0
03 May 2022
Learning through atypical "phase transitions" in overparameterized
  neural networks
Learning through atypical "phase transitions" in overparameterized neural networks
Carlo Baldassi
Clarissa Lauditi
Enrico M. Malatesta
R. Pacelli
Gabriele Perugini
R. Zecchina
18
26
0
01 Oct 2021
Fast Approximation of the Sliced-Wasserstein Distance Using
  Concentration of Random Projections
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections
Kimia Nadjahi
Alain Durmus
Pierre E. Jacob
Roland Badeau
Umut Simsekli
16
36
0
29 Jun 2021
Appearance of Random Matrix Theory in Deep Learning
Appearance of Random Matrix Theory in Deep Learning
Nicholas P. Baskerville
Diego Granziol
J. Keating
13
11
0
12 Feb 2021
Generalisation error in learning with random features and the hidden
  manifold model
Generalisation error in learning with random features and the hidden manifold model
Federica Gerace
Bruno Loureiro
Florent Krzakala
M. Mézard
Lenka Zdeborová
22
165
0
21 Feb 2020
1