A curated list of network embedding techniques.

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

No description provided.

Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)

Code for the paper "Fine-Grained Entity Typing in Hyperbolic Space"

Terraphim AI: deterministic AI Assistant

Learning to represent shortest paths and other graph-based measures of node similarities with graph embeddings

Embedding graphs in symmetric spaces

An implementation of the Watset clustering algorithm in Java.

Implement the node2vec algorithm using Python

An explainable AI system that combines Graph Intelligence, Vector Search, and Retrieval-Augmented Generation (RAG) to deliver grounded answers and transparent reasoning paths. Includes a FastAPI backend, Streamlit UI, FAISS vector index, and an in-memory knowledge graph for hybrid retrieval and recommendations.

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

The SEMB library is an easy-to-use tool for getting and evaluating structural node embeddings in graphs.

GyroSPD: Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices

GitHub repositories and users recommendations by embeddings

Vectorizing knowledge bases for entity linking

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search

An implementation of vdist2vec model in paper A Learning Based Approach to Predict Shortest-Path Distances

Julia package to Compare Graph Embeddings

`arrowspace` for Python. A graph analysis and vector search library

We are applying the notion of the spectral radius to NLP and data represented as graphs.

Experiments on improving the HinDroid model

Code for the Big Data 2019 Paper - Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions

Learning Structural Node Representations using Graph Kernels

:sparkles: Implementation of Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning with pytorch and PyG

Implementation and evaluation of an autonomous SSI-enhanced iSHARE framework, enabling decentralized identity management, schema alignment for property matching, and automated generation of alternative verification requests, improving scalability, privacy, and flexibility in data spaces and SSI ecosystems.

Reconstructed GRU, used to process the graph sequence.

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.