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This code is for the paper "A spatio-temporal deep learning approach for airspace complexity prediction" that is submitted to the TRB

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Welcome to Keras Deep Learning on Graphs (Keras-DGL)

The aim of this keras extension is to provide Sequential and Functional API for performing deep learning tasks on graphs. Specifically, Keras-DGL provides implementation for these particular type of layers,

  • Graph Convolutional Neural Networks (GraphCNN).
  • Graph Attention Convolutional Neural Networks (GraphAttentionCNN).
  • Graph Convolutional Recurrent Neural Networks (GraphConvLSTM).
  • Graph Capsule Convolutional Recurrent Neural Networks (GraphCapsuleCNN) TBD.
  • Graph Message Passing Neural Networks (GraphNeuralNetworks) TBD.
  • Keras-DGL also contains implementation of various graph convolutional filters TBD.

Read the documentation: http://vermaMachineLearning.github.io/keras-deep-graph-learning

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This code is for the paper "A spatio-temporal deep learning approach for airspace complexity prediction" that is submitted to the TRB

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