A curated list of awesome network analysis resources.

A curated list of community detection research papers with implementations.

A general purpose community detection and network embedding library for research built on NetworkX.

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX.

A repository of pretty cool datasets that I collected for network science and machine learning research.

A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).

A Temporal Extension Library for PyTorch Geometric

depthmapX is a multi-platform Spatial Network Analysis Software

Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.

Material for the EPFL master course "A Network Tour of Data Science", edition 2017.

Material for the EPFL master course "A Network Tour of Data Science", edition 2018.

Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis

The AMLSim project is intended to provide a multi-agent based simulator that generates a series of banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing your machine learning models and graph algorithms. We welcome you to enhance this effort since data set is critical to advance our detection capabilities of money laundering activities .

Material for the EPFL master course "A Network Tour of Data Science", edition 2019.

Companion repository for the KDD'18 hands-on tutorial on Higher-Order Data Analytics for Temporal Network Data

Uncertainty and causal emergence in complex networks

Graphs and passing networks in football

TILES: an algorithm for community discovery in dynamic social networks

Software for complex network analysis -- see www.complex-networks.net

Automatically modelling and distilling knowledge within AI. In other words, summarising the AI research firehose.

Prioritizing network communities

A list of data mining and machine learning papers that I implemented in 2019.

A versatile software for modeling epidemics on networks

🌎 Review materials for bioinformatics, computational biology, and science in general

Code for the paper Developing optimal bicycle network growth strategies

Network analysis of the Facebook/Cambridge Analytica scandal

C++ implementation of a MCMC sampler for the (canonical) SBM

Equilibrium Expectation for ERGM parameter estimation for large directed networks

RDyn: graph benchmark handling community dynamics