IdeasLabUT/dynetworkx

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Created over 4 years ago
Updated 2 months ago

IdeasLabUT/dynetworkx

IdeasLabUT

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Python package for importing and analyzing discrete- and continuous-time dynamic networks

Dynamic-Stochastic-Block-Model

MATLAB toolbox for fitting discrete-time dynamic stochastic block models

EDA-Artifact-Detection

Python implementations of machine learning algorithms for motion artifact detection in electrodermal activity (EDA) data

Dynamic-Link-Prediction-Evaluation

MATLAB toolbox for evaluating dynamic link prediction accuracy

CHIP-Network-Model

Python implementation of the CHIP network model, published in NeurIPS 2020.

Latent-Space-Hawkes

Python implementation of the Latent Space Hawkes (LSH) model for continuous-time dynamic networks

Friendship-Interaction-Prediction

MATLAB code for incorporating friendship networks into dynamic link prediction on interaction networks

Continuous-Discrete-Survival-Prediction

Homophily-Aware-Link-Recommendation

SBP-BRiMS-2021-NetworkX-Tutorial

Material from SBP-BRiMS 2021 tutorial "Analyzing Network Data in Python using NetworkX and DyNetworkX"

Jupyter Notebook

Multivariate-Community-Hawkes

Python implementation of the Multivariate Community Hawkes (MULCH) model for continuous-time dynamic networks

WSDM-2022-Challenge

IDEAS Lab UT's submission to the WSDM 2022 Temporal Link Prediction challenge

Jupyter Notebook

Temporal_Motifs_MIDs

Code for analyzing temporal motifs in Militarized Interstate Disputes (MIDs) data

Jupyter Notebook