A unified framework for time-changed Markov processes shows how to accelerate MCMC convergence while preserving the target distribution, unifying several known algorithms.
the time elapsed before the process finally moves from its initial condition ( X0, V0) = ( x0, −1) to x1
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Sampling with time-changed Markov processes
A unified framework for time-changed Markov processes shows how to accelerate MCMC convergence while preserving the target distribution, unifying several known algorithms.