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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…
stat.CO2025
Probabilistic Programming with Sufficient Statistics for faster Bayesian Computation
Clemens Pichler, Jack Jewson, Alejandra Avalos-Pacheco
Probabilistic programming methods have revolutionised Bayesian inference, making it easier than ever for practitioners to perform Markov-chain-Monte-Carlo sampling from non-conjuga…