It is well known that traditional Markov chain Monte Carlo (MCMC) methods can fail to effectively explore the state space for multimodal problems. Parallel tempering is a well-established population ...
Markov Chain Monte Carlo (MCMC) is a family of algorithms which is used to draw samples from arbitrary probability distributions in order to estimate – otherwise intractable – integrals. When the ...
Inference for a complex system with a rough energy landscape is a central topic in Monte Carlo computation. Motivated by the successes of the Wang—Landau algorithm in discrete systems, we generalize ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback