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Explore graph embedding techniques through this 48-minute lecture covering multidimensional scaling on binary data, Laplacian methods, and graph neural networks inspired by DeepWalk and node2vec approaches, while also examining the ethical implications of embedding methods through practical assessment exercises.
Syllabus
L23 - GraphEmbedding
Taught by
UofU Data Science