Machine learning with graphs

graph-based-deep-learning-literature

Библиотеки, работающие с графами:

  • [pyg] pytorch geometric
  • Networkx
  • Scikit-Network
  • graph-tool
  • dgl.ai
  • igraph
  • networkit
  • RAPIDS cuGraph is a monorepo that represents a collection of packages focused on GPU-accelerated graph analytics, including support for property graphs, remote (graph as a service) operations, and graph neural (GNNs). cuGraph supports the creation and manipulation of graphs followed by the execution of scalable fast graph algorithms. Включает nx-cugraph, a [networkx] backend that provides GPU acceleration to NetworkX with zero code change.
  • 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.
  • GraphRAG s a structured, hierarchical approach to Retrieval Augmented Generation (RAG), as opposed to naive semantic-search approaches using plain text snippets. The GraphRAG process involves extracting a knowledge graph out of raw text, building a community hierarchy, generating summaries for these communities, and then leveraging these structures when perform RAG-based tasks.

  • 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]

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