Deep Bottleneck
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Contents
Background
Literature summary
Contributing
User guide
Glossary
Experiments
Indices and tables
API Documentation
Analyses
Indices and tables
Deep Bottleneck
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Welcome to Deep Bottleneck’s documentation!
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Welcome to Deep Bottleneck’s documentation!
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Contents
Background
An introduction to artificial neural networks
Statistical Dependence
How does ‘Statistical Dependance’ help understanding deep learning?
Literature summary
1. On the information bottleneck theory of deep learning (Saxe 2018)
2. Estimating mutual information
3. SVCCA: singular vector canonical correlation analysis
Contributing
Extending the framework
Git workflow
Style Guide
Experiment workflow
Documentation
User guide
Installation
How to use the framework
Glossary
Information Theory Basics
Mathematical Terms in Tishby’s Experiments
Experiments
Description of cohorts
Comparison of infoplanes for different estimators
EDGE individiual runs
Cohort 10
Effect of different initial bias settings for relu
Cohort 13
Cohort 13
Comparison of infoplanes for different estimators and their paramter settings
Cohort 4
Cohort 5
Cohort 9
Indices and tables
API Documentation
deep_bottleneck package
Analyses
Minimal model
Standard vs. Weighted Binning
Tishby’s harmonics dataset
Explore bias towards entropy induced by activation function
Measuring “Information”
Indices and tables
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