/TemporalLinkPrediction

Model for Link prediction in Temporal graph networks using a combination of Graph Convolution, LSTM and Graph Attention Network.

Primary LanguageJupyter Notebook

EvolveGAT

Graph Neural Network model for link prediction in temporal networks.

The architecture is a conjunction of :

  • Graph Convolution network : for graph embedding and reduction in model parameters.
  • Graph Attention network : for enhancing quality of embeddings.
  • LSTM : for processing the temporal graph at each time step.

Model Statistics

  • Training error after 40 epochs : 0.36 (criterion : binary cross entropy).
  • Test AUC score : 0.53.

Links