Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Santoro, Leonardo V."'
We prove the large deviations principle for empirical Bures-Wasserstein barycenters of independent, identically-distributed samples of covariance matrices and covariance operators. As an application, we explore some consequences of our results for th
Externí odkaz:
http://arxiv.org/abs/2409.11384
We develop a statistical framework for conducting inference on collections of time-varying covariance operators (covariance flows) over a general, possibly infinite dimensional, Hilbert space. We model the intrinsically non-linear structure of covari
Externí odkaz:
http://arxiv.org/abs/2310.13764
We establish a strong law of large numbers and a central limit theorem in the Bures-Wasserstein space of covariance operators -- or equivalently centred Gaussian measures -- over a general separable Hilbert space. Specifically, we show that under a m
Externí odkaz:
http://arxiv.org/abs/2305.15592
We develop a generalisation of Mercer's theorem to operator-valued kernels in infinite dimensional Hilbert spaces. We then apply our result to deduce a Karhunen-Lo\`eve theorem, valid for mean-square continuous Hilbertian functional data, i.e. flows
Externí odkaz:
http://arxiv.org/abs/2303.00702
Autor:
Manolescu, Ioan, Santoro, Leonardo V.
We answer the following question: if the occupied (or vacant) set of a planar Poisson Boolean percolation model does contain a crossing of an $n\times n$ square, how wide is this crossing? The answer depends on the whether we consider the critical, s
Externí odkaz:
http://arxiv.org/abs/2211.11661
Publikováno v:
In Stochastic Processes and their Applications January 2024 167
Akademický článek
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