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What is: Temporal Graph Network?

SourceTemporal Graph Networks for Deep Learning on Dynamic Graphs
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

Temporal Graph Network, or TGN, is a framework for deep learning on dynamic graphs represented as sequences of timed events. The memory (state) of the model at time tt consists of a vector si(t)\mathbf{s}_i(t) for each node ii the model has seen so far. The memory of a node is updated after an event (e.g. interaction with another node or node-wise change), and its purpose is to represent the node's history in a compressed format. Thanks to this specific module, TGNs have the capability to memorize long term dependencies for each node in the graph. When a new node is encountered, its memory is initialized as the zero vector, and it is then updated for each event involving the node, even after the model has finished training.