Top 17 graph-embedding open source projects

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

A distributed graph deep learning framework.

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

An ultra-fast, GPU-based large graph embedding algorithm utilizing a novel coarsening algorithm requiring not more than a single GPU.

Y. Zhang, Q. Yao, J. Kwok. Bilinear Scoring Function Search for Knowledge Graph Learning. TPAMI 2022

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

Minimum-distortion embedding with PyTorch

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".

Tri-Party Deep Network Representation, IJCAI-16

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

OpenANE: the first Open source framework specialized in Attributed Network Embedding. The related paper was accepted by Neurocomputing. https://doi.org/10.1016/j.neucom.2020.05.080

Learning node representation using edge semantics

Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).

Mutli-label text classification using ConvNet and graph embedding (Tensorflow implementation)

Graph Embedding via Frequent Subgraphs