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Correlative Information Maximization: A Biologically Plausible Approach
  to Supervised Deep Neural Networks without Weight Symmetry

Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry

7 June 2023
Bariscan Bozkurt
C. Pehlevan
A. Erdogan
ArXivPDFHTML

Papers citing "Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry"

4 / 4 papers shown
Title
Biologically-Motivated Learning Model for Instructed Visual Processing
Biologically-Motivated Learning Model for Instructed Visual Processing
R. Abel
S. Ullman
8
0
0
04 Jun 2023
Correlative Information Maximization Based Biologically Plausible Neural
  Networks for Correlated Source Separation
Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation
Bariscan Bozkurt
Ates Isfendiyaroglu
C. Pehlevan
A. Erdogan
17
1
0
09 Oct 2022
Disentanglement with Biological Constraints: A Theory of Functional Cell
  Types
Disentanglement with Biological Constraints: A Theory of Functional Cell Types
James C. R. Whittington
W. Dorrell
Surya Ganguli
Timothy Edward John Behrens
34
39
0
30 Sep 2022
Polytopic Matrix Factorization: Determinant Maximization Based Criterion
  and Identifiability
Polytopic Matrix Factorization: Determinant Maximization Based Criterion and Identifiability
Gokcan Tatli
A. Erdogan
13
16
0
19 Feb 2022
1