Gradient-based MCMC samplers for dynamic causal modelling

In this technical note, we derive two MCMC (Markov chain Monte Carlo) samplers for dynamic causal models (DCMs). Specifically, we use (a) Hamiltonian MCMC (HMC-E) where sampling is simulated using Hamilton’s equation of motion and (b) Langevin Monte Carlo algorithm (LMC-R and LMC-E) that simulates t...

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Detalles Bibliográficos
Autores principales: Sengupta, Biswa, Friston, Karl J., Penny, Will D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2016
Materias:
Technical Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4692453/
https://www.ncbi.nlm.nih.gov/pubmed/26213349
http://dx.doi.org/10.1016/j.neuroimage.2015.07.043

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4692453/
https://www.ncbi.nlm.nih.gov/pubmed/26213349
http://dx.doi.org/10.1016/j.neuroimage.2015.07.043

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