Sparse stochastic processes identification and sampling

Discrete sample representation of sparse continuous stochastic processes

November 22, 2018 — October 29, 2018

calculus
dynamical systems
geometry
Hilbert space
how do science
Lévy processes
physics
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
time series
uncertainty
Figure 1

Sampling and estimation theory for SDEs driven by Lévy noise, which produces a nice inference theory and gives us a machinery for producing priors for Bayesian sensing problems where the signal is known to be non-Gaussian. I have not got much to say about this yet. In particular, I should say what “sparse” implies in this context. 🚧TODO🚧 clarify

Related maybe, signatures of rough paths.

1 References

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