It looks like there's only one paper in this tag, so it's history isn't too exciting, but you can still check it out below!
October 2023
Edge flows on networks
This paper proposes Gaussian processes for modeling flows on the edges of networks. It introduces principled ways to define priors on edge flows that capture key properties like divergence-freeness and curl-freeness. The method enables separate learning of gradient, curl, and harmonic components.
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