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Estimating Information Flow in Deep Neural Networks
12 October 2018
Ziv Goldfeld
E. Berg
Kristjan Greenewald
Igor Melnyk
Nam H. Nguyen
Brian Kingsbury
Yury Polyanskiy
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Papers citing
"Estimating Information Flow in Deep Neural Networks"
6 / 6 papers shown
Title
Gacs-Korner Common Information Variational Autoencoder
Michael Kleinman
Alessandro Achille
Stefano Soatto
J. Kao
CML
DRL
24
12
0
24 May 2022
Usable Information and Evolution of Optimal Representations During Training
Michael Kleinman
Alessandro Achille
Daksh Idnani
J. Kao
19
13
0
06 Oct 2020
Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation
Ziv Goldfeld
Kristjan Greenewald
Yury Polyanskiy
Jonathan Niles-Weed
21
64
0
30 May 2019
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade
T. Lindeberg
24
19
0
29 May 2019
Minimal Achievable Sufficient Statistic Learning
Milan Cvitkovic
Günther Koliander
17
12
0
19 May 2019
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle
Rana Ali Amjad
Bernhard C. Geiger
21
195
0
27 Feb 2018
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