Analyze Data with Pandas-based Networks. Documentation:

The original library for analyzing multilayer networks.

Python package for simulating spreading phenomena in complex networks

Pruning tool to identify small subsets of network partitions that are significant from the perspective of stochastic block model inference. This method works for single-layer and multi-layer networks, as well as for restricting focus to a fixed number of communities when desired.

First-to-spike decoding in multilayer SNNs.

Predicting Anchor Links between Heterogeneous Social Networks (ASONAM 2016)

A GPU-accelerated generator of a dataset with actors' spreading potentials in multilayer networks under Independent Cascade Model

Image Classification using Deep Neural Networks

TopSpreadersDataset - more than 200 multilayer networks with labelled spreading potentials of their actors

A Graph Optimal Transport Python Package

Methods for identifying and ranking users who alternately behave as contributors and as lurkers over multiple layers of a multilayer social network

Code for the paper "Reconstructuring Sparse Multiplex Networks With Application to Covert Networks"

Experimental repo for the paper: https://doi.org/10.1093/comnet/cnaf036

Supplemental material for paper "Current challenges in multilayer network engineering": Experiment scripts

Deep Network implemented from scratch using only NumPy. This is my interpretation of Dense and Sequential available in the Tensorflow package.

neural network from scratch

OhmNet: Representation learning in multi-layer graphs