most citedPointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior

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math.ST2023★ 1 cited

Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior

Luke Travis, Kolyan Ray

We study pointwise estimation and uncertainty quantification for a sparse variational Gaussian process method with eigenvector inducing variables. For a rescaled Brownian motion pr…

math.ST2023

Semiparametric inference using fractional posteriors

Alice L'Huillier, Luke Travis, Ismaël Castillo +1

We establish a general Bernstein--von Mises theorem for approximately linear semiparametric functionals of fractional posterior distributions based on nonparametric priors. This is…