Pytorch implementation of Deep Variational Information Bottleneck
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Updated
Mar 22, 2018 - Python
Pytorch implementation of Deep Variational Information Bottleneck
Project for the Large Scale Optimization course at Skoltech
A pytorch implementation of DVIB(Deep Variational Information Bottleneck)
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
Implementation of Information Bottleneck with Mutual Information Neural Estimation (MINE)
Microbiome-based disease prediction with multimodal variational information bottlenecks, Grazioli et al., PLOS Computational Biology 2022
PyTorch & OpenMM implementations of deep-learning based approaches for learning and biasing reaction coordinates in molecular simulations.
Official repo for PAC-Bayes Information Bottleneck. ICLR 2022.
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DVIB is an information bottleneck method that tries to disentangle multiview data into shared and private representations.
Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
[ICDE 2022]Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
Information bottleneck's (IB) principle applied to categorical data clustering.
Code for "Attentive Variational Information Bottleneck for TCR-peptide Interaction Prediction", Grazioli et al., Bioinformatics 2022
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.
Official PyTorch implementation of Fully Attentional Networks
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs among Complexity, Leakage, and Utility
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