Bayesian quantile regression extends the classical quantile regression framework by embedding it within a probabilistic paradigm, allowing direct inference on conditional quantiles through ...
Variational inference is a family of optimisation-based methods for approximating complex posterior distributions in Bayesian models. By transforming inference into an optimisation problem, these ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results