3 citations · 8 across the 15 of their papers we have counts for
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Importance Sampling-based Transport Map Hamiltonian Monte Carlo for Bayesian Hierarchical Models
Kjartan Kloster Osmundsen, Tore Selland Kleppe, Roman Liesenfeld
We propose an importance sampling (IS)-based transport map Hamiltonian Monte Carlo procedure for performing full Bayesian analysis in general nonlinear high-dimensional hierarchica…
Saddlepoint-adjusted inversion of characteristic functions
Berent Å. S. Lunde, Tore S. Kleppe, Hans J. Skaug
For certain types of statistical models, the characteristic function (Fourier transform) is available in closed form, whereas the probability density function has an intractable fo…
Dynamically rescaled Hamiltonian Monte Carlo for Bayesian Hierarchical Models
Tore Selland Kleppe
Dynamically rescaled Hamiltonian Monte Carlo (DRHMC) is introduced as a computationally fast and easily implemented method for performing full Bayesian analysis in hierarchical sta…