Graph Representation Insights
Tim and Zach delve into the intricacies of message passing in neural networks and its limitations, drawing parallels to graph isomorphism tests. They discuss the connection between the One WL test and the expressive power of GNNs, shedding light on the complexities of graph representation.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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