Official PyTorch implementation of Fully Attentional Networks
-
Updated
Mar 31, 2023 - Python
8000
Official PyTorch implementation of Fully Attentional Networks
Pytorch implementation of Deep Variational Information Bottleneck
This is the official repository for our CVPR 2023 paper 'Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification'.
Pytorch Implementation of the Nonlinear Information Bottleneck
[ICDE 2022]Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
[ICML'24] Official PyTorch Implementation of TimeX++
Microbiome-based disease prediction with multimodal variational information bottlenecks, Grazioli et al., PLOS Computational Biology 2022
Implementation of Information Bottleneck with Mutual Information Neural Estimation (MINE)
About Codes for ACL 2023 paper: Exploiting! Multimodal Relation Extraction with Feature Denoising and Multimodal Topic Modeling.
[ICMLW 2023, IEEE CISS 2024] Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy
The official repository for AAAI 2024 Oral paper "Structured Probabilistic Coding".
DVIB is an information bottleneck method that tries to disentangle multiview data into shared and private representations.
[NeurIPS] Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes
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.
This repository hosts a progressive series of implementations (Code_v1, Code_v2, and beyond) for deterministic β*-optimization in the Information Bottleneck framework. Includes symbolic fusion, multi-path inference, and Alpay Algebra–driven critical point validation (β* = 4.14144).
Information Bottleneck as Optimisation Method for SSVEP-Based BCI
Synthetic Thalamus is a biologically-inspired neural attention mechanism that mimics the brain's thalamic circuits. This project implements a selective information bottleneck with phase-based synchronization, contrastive learning, and recurrent feedback loops.
Repositório destinado aos arquivos do meu Trabalho de Conclusão de Curso
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.
Add a description, image, and links to the information-bottleneck topic page so that developers can more easily learn about it.
To associate your repository with the information-bottleneck topic, visit your repo's landing page and select "manage topics."