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B-GRASP: A Bayesian Framework for Inferring Graph Weights from SPDE-Inspired Dynamics
We present B-GRASP (Bayesian GRAph inference with SPDE priors), a Bayesian framework for inferring uncertain edge weights in stochastic dynamical systems on graphs from noisy observations of nodal states. The unknown edge weights parameterize the graph differential operator and therefore directly go
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