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We investigate joint graph inference for the chemical and electricalconnectomes of the \textit{Caenorhabditis elegans} roundworm. The\textit{C.elegans} connectomes consist of $253$ non-isolated neurons with knownfunctional attributes, and there are two types of synaptic connectomes,resulting in a pair of graphs. We formulate our joint graph inference from theperspectives of seeded graph matching and joint vertex classification. Ourresults suggest that connectomic inference should proceed in the joint space ofthe two connectomes, which has significant neuroscientific implications.

A Joint Graph Inference Case Study: the C.elegans Chemical and Electrical Connectomes