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A Free-Energy Principle for Representation Learning

A Free-Energy Principle for Representation Learning

27 February 2020
Yansong Gao
Pratik Chaudhari
    DRL
ArXiv (abs)PDFHTML

Papers citing "A Free-Energy Principle for Representation Learning"

6 / 6 papers shown
Title
SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training
SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training
Ildus Sadrtdinov
Ivan Klimov
E. Lobacheva
Dmitry Vetrov
28
0
0
29 May 2025
A picture of the space of typical learnable tasks
A picture of the space of typical learnable tasks
Rahul Ramesh
Jialin Mao
Itay Griniasty
Rubing Yang
H. Teoh
Mark K. Transtrum
James P. Sethna
Pratik Chaudhari
SSLDRL
119
5
0
31 Oct 2022
Towards Understanding Grokking: An Effective Theory of Representation
  Learning
Towards Understanding Grokking: An Effective Theory of Representation Learning
Ziming Liu
O. Kitouni
Niklas Nolte
Eric J. Michaud
Max Tegmark
Mike Williams
AI4CE
98
154
0
20 May 2022
Deep Reference Priors: What is the best way to pretrain a model?
Deep Reference Priors: What is the best way to pretrain a model?
Yansong Gao
Rahul Ramesh
Pratik Chaudhari
BDL
47
5
0
01 Feb 2022
Controllable Guarantees for Fair Outcomes via Contrastive Information
  Estimation
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation
Umang Gupta
Aaron Ferber
B. Dilkina
Greg Ver Steeg
113
58
0
11 Jan 2021
Likelihood Ratio Exponential Families
Likelihood Ratio Exponential Families
Rob Brekelmans
Frank Nielsen
Alireza Makhzani
Aram Galstyan
Greg Ver Steeg
44
6
0
31 Dec 2020
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