Pseudo-marginal Hamiltonian Monte Carlo
Bayesian inference in the presence of an intractable likelihood function is computationally challenging. When following a Markov chain Monte Carlo (MCMC) approach to approximate the posterior distribution in this context, one typically either uses MCMC schemes which target the joint posterior of the...
| Autores principales: | , , |
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| Formato: | Journal article |
| Lenguaje: | English |
| Publicado: |
Journal of Machine Learning Research
2021
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