Temporal Graph Learning in 2023

A new blogpost by Andy Huang, Emanuele Rossi, Michael Galkin, and Kellin Pelrine on the recent progress in temporal Graph ML! Featuring theoretical advancements in understanding expressive power of temporal GNNs, discussing evaluation protocols and trustworthiness concerns, looking at temporal KGs, disease modeling, and anomaly detection, as well as pointing to the software libraries and new datasets!