Influence analysis, for example, is a classic graph-shaped problem; it’s also the core of the use cases that Kocoloski cited.

For 40 years, the Big Five personality model has dominated psychology, but new research suggests it may be incomplete.

Consequently, it became possible to train GNN models on data far exceeding main memory capacity, and training could be up to 95 times faster even on a single GPU server. In particular, the ...

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs.

Caiyan Li, Hongzhe Li, VARIABLE SELECTION AND REGRESSION ANALYSIS FOR GRAPH-STRUCTURED COVARIATES WITH AN APPLICATION TO GENOMICS, The Annals of Applied Statistics, Vol. 4, No. 3 (September 2010), pp.

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the ...

Neo4j, which offers a graph-centric database and related products, announced today that it raised $325 million at a more than $2 billion valuation in a Series F deal led by Eurazeo, with ...