Temporal Graph Learning in 2023. The story so far

In this section, we provide a brief overview of some well-known TGL methods in the literature. There exist two main broad classes of methods for learning on Continuous-Time Dynamic Graphs (CTDGs): Temporal Graph Networks and Walk Aggregating methods. For more details on the formulation of CTDGs, see this survey by Kazemi et al. Temporal Graph Networks (TGNs) generalize Message Passing Neural Networks (MPNNs) to temporal graphs. They do so by introducing a node memory which represents the state of the node at a given time, acting as a compressed representation of the node's past interactions.