5 papers
Posterior contraction rates in Sobolev norms and Bayesian derivative estimation for infinite-dimensional exponential families
Emanuele Dolera, Stefano Favaro, Matteo Giordano
We study posterior contraction in positive-order Sobolev norms and Bayesian derivative estimation for infinite-dimensional exponential families. We embed the natural parameter in a…
Semiparametric Bernstein-von Mises theorems for reversible diffusions
Matteo Giordano, Kolyan Ray
We establish a general semiparametric Bernstein-von Mises theorem for Bayesian nonparametric priors based on continuous observations in a periodic reversible multidimensional diffu…
Dirac mode localization in QCD near the crossover temperature
Matteo Giordano, Tamas G. Kovacs, Ferenc Pittler
We study the localization properties of the low-lying Dirac eigenmodes in QCD near the crossover temperature, using stout-smeared staggered fermions and Symanzik-improved gauge act…
Statistical algorithms for low-frequency diffusion data: A PDE approach
Matteo Giordano, Sven Wang
We consider the problem of making nonparametric inference in a class of multi-dimensional diffusions in divergence form, from low-frequency data. Statistical analysis in this setti…
On strong posterior contraction rates for Besov-Laplace priors in the white noise model
Emanuele Dolera, Stefano Favaro, Matteo Giordano
In this article, we investigate the problem of estimating a spatially inhomogeneous function and its derivatives in the white noise model using Besov-Laplace priors. We show that s…