There are 5 repositories under information-bottleneck topic.
This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.
Pytorch implementation of Deep Variational Information Bottleneck
Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
Official repo for PAC-Bayes Information Bottleneck. ICLR 2022.
Pytorch Implementation of the Nonlinear Information Bottleneck
Microbiome-based disease prediction with multimodal variational information bottlenecks, Grazioli et al., PLOS Computational Biology 2022
Project for the Large Scale Optimization course at Skoltech
Code for "Attentive Variational Information Bottleneck for TCR-peptide Interaction Prediction", Grazioli et al., Bioinformatics 2022
Implementation of Information Bottleneck with Mutual Information Neural Estimation (MINE)
[ICML'24] Official PyTorch Implementation of TimeX++
The official repository for AAAI 2024 Oral paper "Structured Probabilistic Coding"
A pytorch implementation of DVIB(Deep Variational Information Bottleneck)
DVIB is an information bottleneck method that tries to disentangle multiview data into shared and private representations.
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs among Complexity, Leakage, and Utility
[IEEE CISS 2024, ICMLW 2023] Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy
Package for information-theoretic data analysis
Information bottleneck's (IB) principle applied to categorical data clustering.
A Python implementation of the Information Bottleneck analysis framework (Tishby, Pereira, Bialek 2000), especially geared towards the analysis of concrete, finite-size data sets. **GitHub mirror**: development happens at https://gitlab.com/epiasini/embo
A Python library for calculating and visualizing mutual information in neural networks. This repository includes methods to calculate mutual information using various techniques (binning, KDE, Kraskov) and tools to train neural networks and plot information plane dynamics.
Information Bottleneck as Optimisation Method for SSVEP-Based BCI
Modeled discriminative prior problem learning privacy-utility trade-off Private Information Bottleneck un-supervised
This repository contains opensource codes for sparsity inducing approaches in deep information bottleneck models.
PyTorch & OpenMM implementations of deep-learning based approaches for learning and biasing reaction coordinates in molecular simulations.