Nonparanormal graph quilting with applications to calcium imaging
Nonparanormal graph quilting with applications to calcium imaging
Abstract Probabilistic graphical models have become an important unsupervised learning tool for detecting network structures for a variety of problems, including the estimation of functional neuronal connectivity from two‐photon calcium imaging data. However, in the context of calcium imaging, technological limitations only allow for partially overlapping layers of neurons in …