Corpus ID: 5023062

Interacting Particle Markov Chain Monte Carlo

@inproceedings{Rainforth2016InteractingPM,
  title={Interacting Particle Markov Chain Monte Carlo},
  author={Tom Rainforth and Christian A. Naesseth and Fredrik Lindsten and Brooks Paige and Jan-Willem van de Meent and Arnaud Doucet and Frank D. Wood},
  booktitle={ICML},
  year={2016}
}
  • Tom Rainforth, Christian A. Naesseth, +4 authors Frank D. Wood
  • Published in ICML 2016
  • Mathematics, Computer Science
  • We introduce interacting particle Markov chain Monte Carlo (iPMCMC), a PMCMC method based on an interacting pool of standard and conditional sequential Monte Carlo samplers. Like related methods, iPMCMC is a Markov chain Monte Carlo sampler on an extended space. We present empirical results that show significant improvements in mixing rates relative to both noninteracting PMCMC samplers and a single PM-CMC sampler with an equivalent memory and computational budget. An additional advantage of… CONTINUE READING

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    Interacting particle Markov chain Monte Carlo

    • Tom Rainforth, Christian A Naesseth, +4 authors Frank Wood
    • In Proceedings of the 33rd International Conference on Machine Learning,
    • 2016