Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
The statistical physics of graphs and partition functions represents a vibrant intersection of graph theory, statistical mechanics and computational complexity. By summing over an ensemble of ...
Sure, there are graph databases like Neo4j, but graph analysis or graph search may be more useful, depending on the sorts of data relationships you need to explore Graph processing is hot right now in ...
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