3 papers
cs.LG2026
TASTE: Task-Aware Out-of-Distribution Detection via Stein Operators
Michał Kozyra, Gesine Reinert
Out-of-distribution detection methods are often either data-centric, detecting deviations from the training input distribution irrespective of their effect on a trained model, or m…
math.ST2025
Stein's method of moment estimators for local dependency exponential random graph models
Adrian Fischer, Gesine Reinert, Wenkai Xu
Providing theoretical guarantees for parameter estimation in exponential random graph models is a largely open problem. While maximum likelihood estimation has theoretical guarante…
stat.ME2024
A Bayesian mixture model for Poisson network autoregression
Elly Hung, Anastasia Mantziou, Gesine Reinert
In this paper, we propose a new Bayesian Poisson network autoregression mixture model (PNARM). Our model combines ideas from the models of Dahl 2008, Ren et al. 2024 and Armillotta…