Learning laws of stochastic processes

  • Harald Oberhauser (University of Oxford)
E1 05 (Leibniz-Saal)


The sequence of moments characterizes the law of (sufficiently nice) random variables in finite-dimensional spaces. I will talk about an analogous result for path-valued random variables, that is stochastic processes, and develop applications in statistical learning. Our starting point is the so-called signature of a path, that identifies a path as an element in a tensor algebra. (Joint work with Ilya Chevyrev).

4/24/18 3/19/21

Mathematics of Data Seminar

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Katharina Matschke

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