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 ...

Skyler J. Cranmer, Bruce A. Desmarais, Inferential Network Analysis with Exponential Random Graph Models, Political Analysis, Vol. 19, No. 1 (Winter 2011), pp. 66-86 ...

"The model gives us a new perspective on the brain that adds clarity to what we already know about how the brain functions," said Richard Betzel, senior author of a new study in Nature Neuroscience.

This allows you to control the input to the model, resulting in a responsive, easy-to-interrogate natural language interface on top of your graph. The Rise Of The SLM ...

Transfer functions analyze how system output changes depending on the input. This article details how to implement a transfer function in LTspice, comparing ideal vs. modeled ...