ZIYU-DEEP/Awesome-Information-Bottleneck
This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.
This resource is a curated list of research papers about the Information Bottleneck Principle. It helps researchers, particularly those in machine learning and information theory, find key literature on how systems learn by filtering out irrelevant information. It takes in a general research interest in the Information Bottleneck and provides categorized links to academic papers, including classics, reviews, theories, and applications.
393 stars.
Use this if you are an academic researcher or graduate student wanting to explore the Information Bottleneck Principle, its theoretical foundations, and its applications in deep learning and related fields.
Not ideal if you are looking for a practical code library, a tutorial for implementing information bottleneck methods, or a general introduction to machine learning for non-technical users.
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393
Forks
49
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—
License
MIT
Category
Last pushed
Feb 12, 2026
Commits (30d)
0
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