Monte Carlo methods represent the de facto standard for approximating complicated
integrals involving multidimensional target distributions. In order to generate random …

Conditional particle filters (CPFs) are powerful smoothing algorithms for general
nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult …

In this work, we present two novel importance sampling (IS) methods, which can be
considered safe in the sense that they avoid catastrophic scenarios where the IS estimators …