Metropolis-Hastings view on variational inference and adversarial training

ICLR 2019 Kirill NeklyudovEvgenii EgorovPavel ShvechikovDmitry Vetrov

A significant part of MCMC methods can be considered as the Metropolis-Hastings (MH) algorithm with different proposal distributions. From this point of view, the problem of constructing a sampler can be reduced to the question - how to choose a proposal for the MH algorithm?.. (read more)

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