Sparse stochastic processes and sampling

Discrete sample representation of sparse continuous stochastic processes

SDEs driven by Lévy noise have a convenient interpretation in terms of sampling theory, which produces a nice inference theory and gives us a machinery for producing sparse priors for Bayesian sensing problems. I have not got much to say about this yet. In particular I should say what “sparse” implies in this context. 🏗

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