A curated list of network embedding techniques.
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Updated
Dec 8, 2020
A curated list of network embedding techniques.
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Social trust Network Embedding (ICDM 2019)
Learning to represent shortest paths and other graph-based measures of node similarities with graph embeddings
Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)
Embedding graphs in symmetric spaces
From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)
An implementation of the Watset clustering algorithm in Java.
Julia package to Compare Graph Embeddings
GitHub repositories and users recommendations by embeddings
Vectorizing knowledge bases for entity linking
Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)
This repository introduces RezoJDM16K a French Knowledge Graph Dataset with 53 semantic relations created from RezoJDM. Different graph embeddings have gained from this dataset which are available for semantic link prediction task.
The SEMB library is an easy-to-use tool for getting and evaluating structural node embeddings in graphs.
Code for the Big Data 2019 Paper - Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions
An implementation of vdist2vec model in paper A Learning Based Approach to Predict Shortest-Path Distances
Smooth Variational Graph Embeddings for Efficient Neural Architecture Search
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