#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]
Machine Learning Street Talk (MLST)
00:00
Understanding Aggregation and Equivariance in Graph Neural Networks
This chapter explores the key concepts of aggregation and equivariance within Graph Neural Networks, focusing on the interaction and data presentation of nodes. It distinguishes between equivariant and invariant layers, discussing how different operations like summation contribute to the structural integrity and representation in GNN architectures.
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