منابع مشابه
Annealed importance sampling of peptides.
Annealed importance sampling assigns equilibrium weights to a nonequilibrium sample that was generated by a simulated annealing protocol [R. M. Neal, Stat. Comput. 11, 125 (2001)]. The weights may then be used to calculate equilibrium averages, and also serve as an "adiabatic signature" of the chosen cooling schedule. In this paper we demonstrate the method on the 50-atom dileucine peptide and ...
متن کاملAnnealed importance sampling
Abstract. Simulated annealing — moving from a tractable distribution to a distribution of interest via a sequence of intermediate distributions — has traditionally been used as an inexact method of handling isolated modes in Markov chain samplers. Here, it is shown how one can use the Markov chain transitions for such an annealing sequence to define an importance sampler. The Markov chain aspec...
متن کاملAnnealed importance sampling of dileucine peptide
Annealed importance sampling is a means to assign equilibrium weights to a nonequilibrium sample that was generated by a simulated annealing protocol[1]. The weights may then be used to calculate equilibrium averages, and also serve as an “adiabatic signature” of the chosen cooling schedule. In this paper we demonstrate the method on the 50-atom dileucine peptide, showing that equilibrium distr...
متن کاملAnnealed Importance Sampling for Neural Mass Models
Neural Mass Models provide a compact description of the dynamical activity of cell populations in neocortical regions. Moreover, models of regional activity can be connected together into networks, and inferences made about the strength of connections, using M/EEG data and Bayesian inference. To date, however, Bayesian methods have been largely restricted to the Variational Laplace (VL) algorit...
متن کاملAnnealed Importance Sampling for Structure Learning in Bayesian Networks
We present a new sampling approach to Bayesian learning of the Bayesian network structure. Like some earlier sampling methods, we sample linear orders on nodes rather than directed acyclic graphs (DAGs). The key difference is that we replace the usual Markov chain Monte Carlo (MCMC) method by the method of annealed importance sampling (AIS). We show that AIS is not only competitive to MCMC in e...
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ژورنال
عنوان ژورنال: The Journal of Chemical Physics
سال: 2007
ISSN: 0021-9606,1089-7690
DOI: 10.1063/1.2754267