Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities

In this video, I'm introducing our paper titled:
'Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities,' which has been accepted at TMLR 2023.
This work was conducted in collaboration with Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Liò, Franco Scareselli, and Andrea Passerini.

Paper: https://arxiv.org/pdf/2302.01018.pdf

Видео Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities канала Antonio Longa