Project Name	Stars	Most Recent Commit	Open Issues	License	Language
Interviews.ai	3,146	2 years ago	4
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
Hsic Bottleneck	56	3 years ago	2	mit	Python
The HSIC Bottleneck: Deep Learning without Back-Propagation
Unsupervisedattentionmechanism	19	2 years ago			Jupyter Notebook
Code for our paper: "Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers".
Information Theory Deep Learning	15	5 years ago			Jupyter Notebook
Resources and Implementations (PyTorch) for Information Theoretical concepts in Deep Learning
Honest But Curious Nets	14	a year ago		mit	Python
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)
Ndic	14	2 years ago		mit	Python
Neural Distributed Image Compression using Common Information (NDIC)
Dsit	7	2 years ago		mit	Jupyter Notebook
Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"

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Interviews.ai ⭐ 3,146

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.

most recent commit 2 years ago

Hsic Bottleneck ⭐ 56

The HSIC Bottleneck: Deep Learning without Back-Propagation

most recent commit 3 years ago

Unsupervisedattentionmechanism ⭐ 19

Code for our paper: "Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers".

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Information Theory Deep Learning ⭐ 15

Resources and Implementations (PyTorch) for Information Theoretical concepts in Deep Learning

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Honest But Curious Nets ⭐ 14

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)

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Ndic ⭐ 14

Neural Distributed Image Compression using Common Information (NDIC)

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Dsit ⭐ 7

Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"

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