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 flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for graph deep learning. Spektral also includes lots of utilities for representing, manipulating, and transforming graphs in your graph deep learning projects. Spektral is compatible with Python 3.6 and above, and is tested on the latest versions of Ubuntu, MacOS, and Windows. Other Linux distros should work as well. The 1.0 release of Spektral is an important milestone for the library and brings many new features and improvements.

Features

  • Graph Convolutional Networks (GCN)
  • Chebyshev convolutions
  • Edge-Conditioned Convolutions (ECC)
  • Approximated Personalized Propagation of Neural Predictions (APPNP)
  • Graph Isomorphism Networks (GIN)
  • Diffusional Convolutions

Project Samples

Spektral Screenshot 1

Project Activity

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Categories

Networking, Machine Learning, Deep Learning Frameworks

License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Networking Software, Python Machine Learning Software, Python Deep Learning Frameworks

Registered

2022-08-09
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