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 ...
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