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stellargraph avatar

stellargraph/stellargraph

0
View on GitHub↗
3,061 stele·442 fork-uri·Python·Apache-2.0·1 vizualizarestellargraph.readthedocs.io↗

Stellargraph

StellarGraph - Machine Learning on Graphs

Features

  • General Machine Learning - Library for machine learning on graph-structured data.
  • Graph Machine Learning - Machine learning library for graph analysis.
  • Graph Representation Learning - Offers a comprehensive library for machine learning on graph-structured data.
  • Frameworks and Libraries - Library for machine learning on graph-structured data.

Istoric stele

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Întrebări frecvente

Ce face stellargraph/stellargraph?

StellarGraph - Machine Learning on Graphs

Care sunt principalele funcționalități ale stellargraph/stellargraph?

Principalele funcționalități ale stellargraph/stellargraph sunt: General Machine Learning, Graph Machine Learning, Graph Representation Learning, Frameworks and Libraries.

Care sunt câteva alternative open-source pentru stellargraph/stellargraph?

Alternativele open-source pentru stellargraph/stellargraph includ: dmlc/dgl — DGL is a Python library for building and training graph neural networks. It functions as a graph message passing… tflearn/tflearn — tflearn is a deep learning framework and high-level API wrapper for TensorFlow. It provides a toolkit for designing… benedekrozemberczki/karateclub — Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020). benedekrozemberczki/littleballoffur — Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020). chihming/awesome-network-embedding — A curated list of network embedding techniques. morvanzhou/tutorials — This repository is a comprehensive collection of instructional guides and practical examples for Python development,…

Alternative open-source pentru Stellargraph

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  • dmlc/dglAvatar dmlc

    dmlc/dgl

    14,283Vezi pe GitHub↗

    DGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks

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  • chihming/awesome-network-embeddingAvatar chihming

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    A curated list of network embedding techniques.

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  • benedekrozemberczki/karateclubAvatar benedekrozemberczki

    benedekrozemberczki/karateclub

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    Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

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  • benedekrozemberczki/littleballoffurAvatar benedekrozemberczki

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