activity
20142021
most citedSafe-Bayesian Generalized Linear Regression

18 citations · 33 across the 4 of their papers we have counts for

collaborators

6 papers

astro-ph.HE2021★ 2 cited

Researching of magnetic cutoff for local sources of charged particles in the halo of the Galaxy

M. Yu. Khlopov, A. O. Kirichenko, A. G. Mayorov

Models of highly inhomogeneous baryosynthesis of the baryonic asymmetric Universe allow for the existence of macroscopic domains of antimatter, which could evolve in a globular clu…

math.ST2020★ 2 cited

Minimax rates without the fixed sample size assumption

Alisa Kirichenko, Peter Grünwald

We generalize the notion of minimax convergence rate. In contrast to the standard definition, we do not assume that the sample size is fixed in advance. Allowing for varying sample…

math.ST2019★ 18 cited

Safe-Bayesian Generalized Linear Regression

Rianne de Heide, Alisa Kirichenko, Nishant Mehta +1

We study generalized Bayesian inference under misspecification, i.e. when the model is 'wrong but useful'. Generalized Bayes equips the likelihood with a learning rate . We show…

math.ST2017

Minimax lower bounds for function estimation on graphs

Alisa Kirichenko, Harry van Zanten

We study minimax lower bounds for function estimation problems on large graph when the target function is smoothly varying over the graph. We derive minimax rates in the context of…

math.ST2015

Estimating a smooth function on a large graph by Bayesian Laplacian regularisation

Alisa Kirichenko, Harry van Zanten

We study a Bayesian approach to estimating a smooth function in the context of regression or classification problems on large graphs. We derive theoretical results that show how as…

math.ST2014★ 11 cited

Optimality of Poisson processes intensity learning with Gaussian processes

Alisa Kirichenko, Harry van Zanten

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 -dime…