Post #547

Recordings: Graph Neural Networks at CAIMS Recordings of a session at CAIMS are now available. The topics are the cutting-edge research in the GNN world and is interesting if you want to see what researchers are currently working on in this space. From local structures to size generalization in graph neural networks by Haggai Maron (NVIDIA) On the generalization of graph neural networks and their applications to probabilistic inference by Renjie Liao (Google) Graph convolution for semi-supervised classification: improved linear separability and out-of-distribution generalization by Kimon Fountoulakis (University of Waterloo) Persistent message passing by Petar Veličković (DeepMind)