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Local convexity of the TAP free energy and AMP convergence for
  Z2-synchronization

Local convexity of the TAP free energy and AMP convergence for Z2-synchronization

21 June 2021
Michael Celentano
Z. Fan
Song Mei
    FedML
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Papers citing "Local convexity of the TAP free energy and AMP convergence for Z2-synchronization"

9 / 9 papers shown
Title
U-Nets as Belief Propagation: Efficient Classification, Denoising, and
  Diffusion in Generative Hierarchical Models
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models
Song Mei
3DV
AI4CE
DiffM
39
11
0
29 Apr 2024
Approximate message passing from random initialization with applications
  to $\mathbb{Z}_{2}$ synchronization
Approximate message passing from random initialization with applications to Z2\mathbb{Z}_{2}Z2​ synchronization
Gen Li
Wei Fan
Yuting Wei
26
10
0
07 Feb 2023
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the
  TAP free energy
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy
Michael Celentano
26
20
0
19 Aug 2022
The TAP free energy for high-dimensional linear regression
The TAP free energy for high-dimensional linear regression
Jia Qiu
Subhabrata Sen
17
8
0
14 Mar 2022
Approximate Message Passing for orthogonally invariant ensembles:
  Multivariate non-linearities and spectral initialization
Approximate Message Passing for orthogonally invariant ensembles: Multivariate non-linearities and spectral initialization
Xinyi Zhong
Tianhao Wang
Zhou-Yang Fan
27
20
0
05 Oct 2021
The replica-symmetric free energy for Ising spin glasses with
  orthogonally invariant couplings
The replica-symmetric free energy for Ising spin glasses with orthogonally invariant couplings
Z. Fan
Yihong Wu
27
15
0
06 May 2021
A spin-glass model for the loss surfaces of generative adversarial
  networks
A spin-glass model for the loss surfaces of generative adversarial networks
Nicholas P. Baskerville
J. Keating
F. Mezzadri
J. Najnudel
GAN
28
12
0
07 Jan 2021
The Lasso with general Gaussian designs with applications to hypothesis
  testing
The Lasso with general Gaussian designs with applications to hypothesis testing
Michael Celentano
Andrea Montanari
Yuting Wei
42
63
0
27 Jul 2020
Asymptotic normality of maximum likelihood and its variational
  approximation for stochastic blockmodels
Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels
Peter J. Bickel
David S. Choi
Xiangyu Chang
Hai Zhang
60
220
0
04 Jul 2012
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