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MetFlow: A New Efficient Method for Bridging the Gap between Markov
  Chain Monte Carlo and Variational Inference

MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference

27 February 2020
Achille Thin
Nikita Kotelevskii
Jean-Stanislas Denain
Léo Grinsztajn
Alain Durmus
Maxim Panov
Eric Moulines
    BDL
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Papers citing "MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference"

3 / 3 papers shown
Title
Optimization of Annealed Importance Sampling Hyperparameters
Optimization of Annealed Importance Sampling Hyperparameters
Shirin Goshtasbpour
Fernando Perez-Cruz
27
1
0
27 Sep 2022
A general perspective on the Metropolis-Hastings kernel
A general perspective on the Metropolis-Hastings kernel
Christophe Andrieu
Anthony Lee
Samuel Livingstone
31
24
0
29 Dec 2020
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,267
0
09 Jun 2012
1