The Information Bottleneck Method by Tishby, Pereira, and Bialek is an interesting way to look at what is happening in a deep neural network. You can see the concept explained in following papers
- Deep Learning and the Information Bottleneck Principle , and
- ON THE INFORMATION BOTTLENECK THEORY OF DEEP LEARNING
Professor Tishby also does a nice lecture on the topic in
Information Theory of Deep Learning. Naftali Tishby
With a follow-on alk with more detail:
Information Theory of Deep Learning - Naftali Tishby
Deep learning aside, there are other interesting applications of the bottleneck method. It can be used to categorize music chords:
Information bottleneck web applet tutorial for categorizing music chords
and in this talk, the method is used to quantify prediction in the brain
Stephanie Palmer: "Information bottleneck approaches to quantifying prediction in the brain"
I found the following talk also interesting simplified version of the concept applied to deterministic mappings:
The Deterministic Information Bottleneck
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