Machine learning with graphs

Библиотеки, работающие с графами:

[pyg] pytorch geometric
Networkx
Scikit-Network
graph-tool
dgl.ai
igraph
networkit
SNAP
deep snap
GraphGym. GraphGym is a platform for designing and evaluating Graph Neural Networks (GNN)
Stellar Graph Machine Learning on Graphs
Neo4j Graph Algorithms
[apache-spark] Unified engine for large-scale data analytics
[apache-tinkertop-and-gremlin] Apache TinkerPop™ is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP)
SciGraph Represent ontologies and ontology-encoded knowledge in a [neo4j] graph.
Бенчмарк
Community detection for NetworkX Louvain Community Detection
CSRGraphs - Fast and memory efficient library for large read-only graphs
nodevectors some alghoritms, depends on CSRGraphs
torchpr (Personalized) Page-Rank computation using PyTorch
karateclub is an unsupervised machine learning extension library for NetworkX
GraphWorld toolbox for graph learning researchers to systematically test new models on synthetic graph datasets. More info
GraphGalery GraphGallery is a gallery for benchmarking Graph Neural Networks (GNNs)
Large graphs datasets
Tools created by the OSoMe team

Graph [bd]

[neo4j]
[dgraph]
[janus-graph]
TigerGraphDB The First Native Parallel Graph (NPG)
Ontotext GraphDB. RDF Database for Knowledge Graphs. docker
UKV. UKV is an open C-layer binary standard for “Create, Read, Update, Delete” operations, or CRUD for short.
Tom Sawyer Graph Database Browser
Neo4j web brouser dedicated installation

Смотри еще: