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stat.ME2025
Bayesian computation for high-dimensional Gaussian Graphical Models with spike-and-slab priors
Deborah Sulem, Jack Jewson, David Rossell
Gaussian graphical models are widely used to infer dependence structures. Bayesian methods are appealing to quantify uncertainty associated with structural learning, i.e., the plau…
math.ST2025
Estimation in linear high dimensional Hawkes processes: a Bayesian approach
Judith Rousseau, Vincent Rivoirard, Déborah Sulem
In this paper we study the frequentist properties of Bayesian approaches in linear high dimensional Hawkes processes in a sparse regime where the number of interaction functions ac…