41 citations · 71 across the 7 of their papers we have counts for
9 papers
Position: agentic AI orchestration should be Bayes-consistent
Theodore Papamarkou, Pierre Alquier, Matthias Bauer +27
LLMs excel at predictive tasks and complex reasoning tasks, but many high-value deployments rely on decisions under uncertainty, for example, which tool to call, which expert to co…
Power-Expected-Posterior Priors as Mixtures of g-Priors
Dimitris Fouskakis, Ioannis Ntzoufras
One of the main approaches used to construct prior distributions for objective Bayes methods is the concept of random imaginary observations. Under this setup, the expected-posteri…
Variations of Power-Expected-Posterior Priors in Normal Regression Models
Dimitris Fouskakis, Ioannis Ntzoufras, Konstantinos Perrakis
The power-expected-posterior (PEP) prior is an objective prior for Gaussian linear models, which leads to consistent model selection inference, under the M-closed scenario, and ten…
Power-Expected-Posterior Priors for Generalized Linear Models
Dimitris Fouskakis, Ioannis Ntzoufras, Konstantinos Perrakis
The power-expected-posterior (PEP) prior provides an objective, automatic, consistent and parsimonious model selection procedure. At the same time it resolves the conceptual and co…
Bayesian transformation family selection: moving towards a transformed Gaussian universe
Efstratia Charitidou, Dimitris Fouskakis, Ioannis Ntzoufras
The problem of transformation selection is thoroughly treated from a Bayesian perspective. Several families of transformations are considered with a view to achieving normality: th…
Power-Conditional-Expected Priors: Using g-priors with Random Imaginary Data for Variable Selection
Dimitris Fouskakis, Ioannis Ntzoufras
The Zellner's g-prior and its recent hierarchical extensions are the most popular default prior choices in the Bayesian variable selection context. These prior set-ups can be expre…