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Recurrent Event Network : Global Structure Inference Over Temporal Knowledge Graph
We present Recurrent Event Network (RE-Net), a novel autoregressive architecture for modeling temporal sequences of multi-relational graphs (e. g., temporal knowledge graph), which can perform sequential, global structure inference over future time stamps to predict new events.
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