Understanding Autoencoders with Information Theoretic Concepts

30 March 2018

Papers citing "Understanding Autoencoders with Information Theoretic Concepts"

12 / 12 papers shown

Title
MOLE: MOdular Learning FramEwork via Mutual Information Maximization Tianchao Li Yulong Pei 25 0 0 15 Aug 2023
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study Luis P. Silvestrin Shujian Yu Mark Hoogendoorn OOD 18 1 0 17 Jul 2023
Local Intrinsic Dimensional Entropy Rohan Ghosh Mehul Motani 15 2 0 05 Apr 2023
Pain level and pain-related behaviour classification using GRU-based sparsely-connected RNNs Mohammad Mahdi Dehshibi Temitayo A. Olugbade F. Díaz-de-María N. Bianchi-Berthouze Ana Tajadura-Jiménez 21 10 0 20 Dec 2022
Self-Adaptive, Dynamic, Integrated Statistical and Information Theory Learning Z. Viharos Ágnes Szücs 14 1 0 21 Nov 2022
Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning Thanh-Dung Le R. Noumeir J. Rambaud Guillaume Sans P. Jouvet 19 7 0 26 Sep 2022
Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysis P. Braca L. Millefiori A. Aubry S. Maranò A. De Maio P. Willett 27 12 0 22 Jul 2022
Mutual information estimation for graph convolutional neural networks Marius Cervera Landsverk S. Riemer-Sørensen SSL GNN 15 1 0 31 Mar 2022
On Information Plane Analyses of Neural Network Classifiers -- A Review Bernhard C. Geiger 13 50 0 21 Mar 2020
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels Kristoffer Wickstrøm Sigurd Løkse Michael C. Kampffmeyer Shujian Yu José C. Príncipe Robert Jenssen 11 31 0 25 Sep 2019
Partial Or Complete, That's The Question Qiang Ning Hangfeng He Chuchu Fan Dan Roth 22 15 0 12 Jun 2019
An Introduction to Deep Learning for the Physical Layer Tim O'Shea J. Hoydis AI4CE 87 2,158 0 02 Feb 2017