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Entropic alternatives to initialization

Entropic alternatives to initialization

16 July 2021
Daniele Musso
ArXivPDFHTML

Papers citing "Entropic alternatives to initialization"

15 / 15 papers shown
Title
Towards quantifying information flows: relative entropy in deep neural
  networks and the renormalization group
Towards quantifying information flows: relative entropy in deep neural networks and the renormalization group
J. Erdmenger
Kevin T. Grosvenor
R. Jefferson
59
17
0
14 Jul 2021
Partial local entropy and anisotropy in deep weight spaces
Partial local entropy and anisotropy in deep weight spaces
Daniele Musso
11
3
0
17 Jul 2020
A scale-dependent notion of effective dimension
A scale-dependent notion of effective dimension
Oksana Berezniuk
Alessio Figalli
Raffaele Ghigliazza
Kharen Musaelian
25
24
0
29 Jan 2020
Mean-field inference methods for neural networks
Mean-field inference methods for neural networks
Marylou Gabrié
AI4CE
41
33
0
03 Nov 2019
Properties of the geometry of solutions and capacity of multi-layer
  neural networks with Rectified Linear Units activations
Properties of the geometry of solutions and capacity of multi-layer neural networks with Rectified Linear Units activations
Carlo Baldassi
Enrico M. Malatesta
R. Zecchina
MLT
6
43
0
17 Jul 2019
Shaping the learning landscape in neural networks around wide flat
  minima
Shaping the learning landscape in neural networks around wide flat minima
Carlo Baldassi
Fabrizio Pittorino
R. Zecchina
MLT
30
82
0
20 May 2019
Improved Regularization of Convolutional Neural Networks with Cutout
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
63
3,739
0
15 Aug 2017
Opening the Black Box of Deep Neural Networks via Information
Opening the Black Box of Deep Neural Networks via Information
Ravid Shwartz-Ziv
Naftali Tishby
AI4CE
61
1,399
0
02 Mar 2017
Deep Information Propagation
Deep Information Propagation
S. Schoenholz
Justin Gilmer
Surya Ganguli
Jascha Narain Sohl-Dickstein
39
363
0
04 Nov 2016
Unreasonable Effectiveness of Learning Neural Networks: From Accessible
  States and Robust Ensembles to Basic Algorithmic Schemes
Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes
Carlo Baldassi
C. Borgs
J. Chayes
Alessandro Ingrosso
Carlo Lucibello
Luca Saglietti
R. Zecchina
40
166
0
20 May 2016
Local entropy as a measure for sampling solutions in Constraint
  Satisfaction Problems
Local entropy as a measure for sampling solutions in Constraint Satisfaction Problems
Carlo Baldassi
Alessandro Ingrosso
Carlo Lucibello
Luca Saglietti
R. Zecchina
29
57
0
18 Nov 2015
Subdominant Dense Clusters Allow for Simple Learning and High
  Computational Performance in Neural Networks with Discrete Synapses
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses
Carlo Baldassi
Alessandro Ingrosso
Carlo Lucibello
Luca Saglietti
R. Zecchina
32
127
0
18 Sep 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
95
18,534
0
06 Feb 2015
Deep learning with Elastic Averaging SGD
Deep learning with Elastic Averaging SGD
Sixin Zhang
A. Choromańska
Yann LeCun
FedML
38
609
0
20 Dec 2014
Revisiting Natural Gradient for Deep Networks
Revisiting Natural Gradient for Deep Networks
Razvan Pascanu
Yoshua Bengio
ODL
78
388
0
16 Jan 2013
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