1 citations · 1 across the 1 of their papers we have counts for
3 papers
stat.CO2021★ 1 cited
Sampling from high-dimensional, multimodal distributions using automatically tuned, tempered Hamiltonian Monte Carlo
Joonha Park
Hamiltonian Monte Carlo (HMC) is widely used for sampling from high dimensional target distributions with densities known up to proportionality. While HMC exhibits favorable scalin…
stat.CO2019
Markov chain Monte Carlo algorithms with sequential proposals
Joonha Park, Yves F. Atchadé
We explore a general framework in Markov chain Monte Carlo (MCMC) sampling where sequential proposals are tried as a candidate for the next state of the Markov chain. This sequenti…
stat.ME2017
Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter
Joonha Park, Edward L. Ionides
We propose a method for inference on moderately high-dimensional, nonlinear, non-Gaussian, partially observed Markov process models for which the transition density is not analytic…