3 papers
stat.CO2026
Bayesian score calibration for approximate models
Joshua J Bon, David J Warne, David J Nott +1
Scientists continue to develop increasingly complex mechanistic models to reflect their knowledge more realistically. Statistical inference using these models can be challenging si…
stat.CO2025
Knots and variance ordering of sequential Monte Carlo algorithms
Joshua J Bon, Anthony Lee
Sequential Monte Carlo algorithms, or particle filters, are widely used for approximating intractable integrals, particularly those arising in Bayesian inference and state-space mo…
stat.ME2025
A Principled Approach to Bayesian Transfer Learning
Adam Bretherton, Joshua J. Bon, David J. Warne +2
Updating information given some observed data is the core tenet of Bayesian inference. Bayesian transfer learning extends this idea by incorporating information…