pykeen
🤖 A Python library for learning and evaluating knowledge graph embeddings
road-network-link-prediction
Research work which explores the application of link prediction methods on road networks.
https://github.com/cpu-ds/unike
基于 OpenKE-PyTorch 开发的知识图谱嵌入工具包,支持跨平台运行,具备自动超参数搜索、高效并行训练以及实验结果记录功能,为研究与应用提供强大助力。
https://github.com/aida-ugent/maxentcomb
Source code for the paper "Block-Approximated Exponential Random Graphs" (DSAA2020)
https://github.com/april-tools/gekcs
How to Turn Your Knowledge Graph Embeddings into Generative Models
https://github.com/breandan/tracelink
🔗 Trace Link Prediction from code to documentation
https://github.com/aida-ugent/fipr
The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer (ECML-PKDD 2021).
webknograph
WebKnoGraph is an open research project that uses data processing, vector embeddings, and graph algorithms to optimize internal linking at scale. Built for both academic and industry use, it offers THE FIRST FULLY transparent, AI-driven framework for improving SEO and site navigation through reproducible methods.
https://github.com/aida-ugent/nrl4lp
Instructions for replicating the experiments in the paper "Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?" (DSAA2020)
https://github.com/astrazeneca/ness
Official implementation of "NESS: Node Embeddings from Static Subgraphs"
GEM
GEM: A Python package for graph embedding methods - Published in JOSS (2018)
torch-rgcn
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
midi2vec
MIDI2vec computes embeddings for representing MIDI data in vector space