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Graph Neural Networks (GNNs) are a class of deep learning methods designed to perform inference on data described by graphs. GNNs are neural ...

18.11.2021 · Which are the best open-source graph-neural-network projects? This list will help you: pytorch_geometric, dgl, euler, spektral, SuperGluePretrainedNetwork, RecBole, and pytorch_geometric_temporal.

Library for deep learning on graphs. ... DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph ...

Browse The Most Popular 3 Graph Neural Networks Torch Open Source Projects

Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but ...

Deep Learning. Course: Deep Learning. View on GitHub · Course (Deep Learning): Deep Learning Tutorials TensorFlow Tutorials Graph Neural Networks Projects Data ...

Best 191 Graph Neural Networks Open Source Projects · Pytorch Geometric · Dgl · Graph Based Deep Learning Literature · Euler · Stellargraph · Spektral · Benchmarking ...

Euler ⭐ 2,246. A distributed graph deep learning framework. Stellargraph ⭐ 2,227. StellarGraph - Machine Learning on Graphs. Spektral ⭐ 1,941. Graph Neural Networks with Keras and Tensorflow 2. Benchmarking Gnns ⭐ 1,622. Repository for benchmarking graph neural networks. Recbole ⭐ 1,504.

Click to see the best open source graph neural networks code project including an engine, API, generator, and tools.

Efficient Graph Neural Networks - a curated list of papers and projects - GitHub - chaitjo/awesome-efficient-gnn: Efficient Graph Neural Networks - a ...

The Top 596 Graph Neural Networks Open Source Projects on Github. Topic > Graph Neural Networks. Pytorch_geometric ⭐ 13,442 · Graph Neural Network Library ...