Transformers vs GNNs
Tim and Zach delve into the comparison between transformers and GNNs, emphasizing the importance of graph relationships in learning efficiency. They explore the significance of message passing and the potential for rewiring techniques to enhance GNN architectures, highlighting the role of inductive priors in optimizing information flow.In this clip
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Machine Learning Street Talk (MLST)
#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]
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