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 ...
A KAIST research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. Named as T-GPS (Trillion-scale ...
The team proposed propose a novel entity-type-enriched cascaded neural network (E 2 CNN) that considers the overlap triple problem and entity-type information to construct a Chinese financial ...
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