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08/30/2022
Besov priors in density estimation: optimal posterior contraction rates and adaptation
Besov priors are nonparametric priors that model spatially inhomogeneous...
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05/16/2022
On the inability of Gaussian process regression to optimally learn compositional functions
We rigorously prove that deep Gaussian process priors can outperform Gau...
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12/22/2020
Nonparametric Bayesian inference for reversible multi-dimensional diffusions
We study nonparametric Bayesian modelling of reversible multi-dimensiona...
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10/16/2019
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
For O a bounded domain in R^d and a given smooth function g:O→R, we cons...
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11/09/2018
