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Interneurons accelerate learning dynamics in recurrent neural networks
  for statistical adaptation

Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation

21 September 2022
David Lipshutz
Cengiz Pehlevan
D. Chklovskii
ArXivPDFHTML

Papers citing "Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation"

16 / 16 papers shown
Title
VICReg: Variance-Invariance-Covariance Regularization for
  Self-Supervised Learning
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Adrien Bardes
Jean Ponce
Yann LeCun
SSL
DML
118
917
0
11 May 2021
On Feature Decorrelation in Self-Supervised Learning
On Feature Decorrelation in Self-Supervised Learning
Tianyu Hua
Wenxiao Wang
Zihui Xue
Sucheng Ren
Yue Wang
Hang Zhao
SSL
OOD
163
192
0
02 May 2021
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar
Li Jing
Ishan Misra
Yann LeCun
Stéphane Deny
SSL
239
2,321
0
04 Mar 2021
A simple normative network approximates local non-Hebbian learning in
  the cortex
A simple normative network approximates local non-Hebbian learning in the cortex
Siavash Golkar
David Lipshutz
Yanis Bahroun
Anirvan M. Sengupta
D. Chklovskii
OffRL
30
15
0
23 Oct 2020
Biologically plausible single-layer networks for nonnegative independent
  component analysis
Biologically plausible single-layer networks for nonnegative independent component analysis
David Lipshutz
Cengiz Pehlevan
D. Chklovskii
36
11
0
23 Oct 2020
A biologically plausible neural network for multi-channel Canonical
  Correlation Analysis
A biologically plausible neural network for multi-channel Canonical Correlation Analysis
David Lipshutz
Yanis Bahroun
Siavash Golkar
Anirvan M. Sengupta
Dmitri B. Chkovskii
24
23
0
01 Oct 2020
Whitening for Self-Supervised Representation Learning
Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov
Aliaksandr Siarohin
E. Sangineto
N. Sebe
SSL
68
310
0
13 Jul 2020
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural
  Networks
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks
Gauthier Gidel
Francis R. Bach
Simon Lacoste-Julien
AI4CE
53
153
0
30 Apr 2019
A mathematical theory of semantic development in deep neural networks
A mathematical theory of semantic development in deep neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
60
264
0
23 Oct 2018
Decorrelated Batch Normalization
Decorrelated Batch Normalization
Lei Huang
Dawei Yang
B. Lang
Jia Deng
34
192
0
23 Apr 2018
On the Optimization of Deep Networks: Implicit Acceleration by
  Overparameterization
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
Sanjeev Arora
Nadav Cohen
Elad Hazan
91
481
0
19 Feb 2018
Blind nonnegative source separation using biological neural networks
Blind nonnegative source separation using biological neural networks
Cengiz Pehlevan
S. Mohan
D. Chklovskii
105
38
0
01 Jun 2017
Why do similarity matching objectives lead to Hebbian/anti-Hebbian
  networks?
Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks?
Cengiz Pehlevan
Anirvan M. Sengupta
D. Chklovskii
28
78
0
23 Mar 2017
Optimal whitening and decorrelation
Optimal whitening and decorrelation
A. Kessy
A. Lewin
K. Strimmer
42
403
0
02 Dec 2015
A Normative Theory of Adaptive Dimensionality Reduction in Neural
  Networks
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Cengiz Pehlevan
D. Chklovskii
34
53
0
30 Nov 2015
Exact solutions to the nonlinear dynamics of learning in deep linear
  neural networks
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
ODL
136
1,830
0
20 Dec 2013
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