Approaching problems with data-driven models often requires reliable uncertainty estimates. Bayesian neural networks can offer these for deep learning models. Without the knowledge to set informative ...
Monte Carlo sampling methods form a cornerstone of contemporary statistical inference by enabling the approximation of complex integrals and posterior distributions that defy analytical solution. At ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results