Graph networks can model data observed across different levels of biological systems that span from population graphs (with patients as network nodes) to molecular graphs that involve omics data.

The era of "data deluge" has sparked the interest in graph-based learning methods in a number of disciplines such as sociology, biology, neuroscience, or engineering. In this paper, we introduce a ...

A dataflow architecture for universal graph neural network inference via multi-queue streaming. - sharc-lab/FlowGNN ...