Top 8 node-embedding open source projects

A collection of important graph embedding, classification and representation learning papers with implementations.

An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".

An alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".

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

New Algorithms for Learning on Hypergraphs

Representation learning-based graph alignment based on implicit matrix factorization and structural embeddings