Graph Embeddings and PyTorch-BigGraph

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15 Nov 2021

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This video provides an overview of Graph Embeddings and how PyTorch-BigGraph enables learning graph embeddings for very large graphs. The key challenge with this is you would need a lot of memory to store the vectors for each node in a large graph. To solve this, BigGraph uses novel partitioning, distributed execution, and negative sampling algorithms. I hope this is a decent introduction to graph embeddings and PyTorch-BigGraph, really excited about the upcoming release of the Wikidata Weaviate web demo! PyTorch-BigGraph (blog post) - PyTorch-BigGraph (paper) - Paperswithdata (graph filter) -

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