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Safe-Bayesian Generalized Linear Regression
We study generalized Bayesian inference under misspecification, i. e. when the model is 'wrong but useful'.
Optimality of Poisson processes intensity learning with Gaussian processes
In this paper we provide theoretical support for the so-called "Sigmoidal Gaussian Cox Process" approach to learning the intensity of an inhomogeneous Poisson process on a $d$-dimensional domain.
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