Alert button
Picture for Naftali Tishby

Naftali Tishby

Alert button

Intrinsic Motivation in Dynamical Control Systems

Dec 29, 2022
Stas Tiomkin, Ilya Nemenman, Daniel Polani, Naftali Tishby

Figure 1 for Intrinsic Motivation in Dynamical Control Systems
Figure 2 for Intrinsic Motivation in Dynamical Control Systems
Figure 3 for Intrinsic Motivation in Dynamical Control Systems
Figure 4 for Intrinsic Motivation in Dynamical Control Systems
Viaarxiv icon

Detecting chaos in lineage-trees: A deep learning approach

Jun 08, 2021
Hagai Rappeport, Irit Levin Reisman, Naftali Tishby, Nathalie Q. Balaban

Figure 1 for Detecting chaos in lineage-trees: A deep learning approach
Figure 2 for Detecting chaos in lineage-trees: A deep learning approach
Figure 3 for Detecting chaos in lineage-trees: A deep learning approach
Figure 4 for Detecting chaos in lineage-trees: A deep learning approach
Viaarxiv icon

The Dual Information Bottleneck

Jun 08, 2020
Zoe Piran, Ravid Shwartz-Ziv, Naftali Tishby

Figure 1 for The Dual Information Bottleneck
Figure 2 for The Dual Information Bottleneck
Figure 3 for The Dual Information Bottleneck
Figure 4 for The Dual Information Bottleneck
Viaarxiv icon

Semantic categories of artifacts and animals reflect efficient coding

May 11, 2019
Noga Zaslavsky, Terry Regier, Naftali Tishby, Charles Kemp

Figure 1 for Semantic categories of artifacts and animals reflect efficient coding
Figure 2 for Semantic categories of artifacts and animals reflect efficient coding
Figure 3 for Semantic categories of artifacts and animals reflect efficient coding
Figure 4 for Semantic categories of artifacts and animals reflect efficient coding
Viaarxiv icon

An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis

Oct 31, 2018
Amichai Painsky, Meir Feder, Naftali Tishby

Figure 1 for An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis
Figure 2 for An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis
Figure 3 for An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis
Figure 4 for An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis
Viaarxiv icon

Efficient human-like semantic representations via the Information Bottleneck principle

Aug 09, 2018
Noga Zaslavsky, Charles Kemp, Terry Regier, Naftali Tishby

Figure 1 for Efficient human-like semantic representations via the Information Bottleneck principle
Figure 2 for Efficient human-like semantic representations via the Information Bottleneck principle
Figure 3 for Efficient human-like semantic representations via the Information Bottleneck principle
Figure 4 for Efficient human-like semantic representations via the Information Bottleneck principle
Viaarxiv icon

Color naming reflects both perceptual structure and communicative need

Aug 03, 2018
Noga Zaslavsky, Charles Kemp, Naftali Tishby, Terry Regier

Figure 1 for Color naming reflects both perceptual structure and communicative need
Figure 2 for Color naming reflects both perceptual structure and communicative need
Figure 3 for Color naming reflects both perceptual structure and communicative need
Figure 4 for Color naming reflects both perceptual structure and communicative need
Viaarxiv icon

A General Memory-Bounded Learning Algorithm

Dec 10, 2017
Michal Moshkovitz, Naftali Tishby

Viaarxiv icon

Gaussian Lower Bound for the Information Bottleneck Limit

Nov 07, 2017
Amichai Painsky, Naftali Tishby

Figure 1 for Gaussian Lower Bound for the Information Bottleneck Limit
Figure 2 for Gaussian Lower Bound for the Information Bottleneck Limit
Figure 3 for Gaussian Lower Bound for the Information Bottleneck Limit
Figure 4 for Gaussian Lower Bound for the Information Bottleneck Limit
Viaarxiv icon

Opening the Black Box of Deep Neural Networks via Information

Apr 29, 2017
Ravid Shwartz-Ziv, Naftali Tishby

Figure 1 for Opening the Black Box of Deep Neural Networks via Information
Figure 2 for Opening the Black Box of Deep Neural Networks via Information
Figure 3 for Opening the Black Box of Deep Neural Networks via Information
Figure 4 for Opening the Black Box of Deep Neural Networks via Information
Viaarxiv icon