Background: survey on GNNs. 10% systems, 60% applications, 30% theory. Aim to provide more systems-focused direction.
Talks
Graph Neural Networks For Learning About Never Before Seen PhenomenaGraphcore’s IPU and GNNsGraph Representation Learning for Chip DesignHigh Performance GNNs in JAXMachine Learning on Dynamic Graphs: Temporal Graph Networks‪Efficient GNNs: How Can Graphs Go From Last To Fast?Graph Neural Networks: Moving from Research to Commercial Applications