Layered adaptive importance sampling
Monte Carlo methods represent the de facto standard for approximating complicated
integrals involving multidimensional target distributions. In order to generate random …
integrals involving multidimensional target distributions. In order to generate random …
Conditional particle filters with diffuse initial distributions
S Karppinen, M Vihola - Statistics and Computing, 2021 - Springer
Conditional particle filters (CPFs) are powerful smoothing algorithms for general
nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult …
nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult …
Safe importance sampling based on partial posteriors and neural variational approximations
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 …
considered safe in the sense that they avoid catastrophic scenarios where the IS estimators …