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Gradient-free MCMC methods for dynamic causal modelling
In this technical note we compare the performance of four gradient-free MCMC samplers (random walk Metropolis sampling, slice-sampling, adaptive MCMC sampling and population-based MCMC sampling with tempering) in terms of the number of independent samples they can produce per unit computational time...
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| Pubblicato in: | Neuroimage |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Academic Press
2015
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4410946/ https://ncbi.nlm.nih.gov/pubmed/25776212 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2015.03.008 |
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