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We develop a method to combine Markov chain Monte Carlo (MCMC) and variational inference (VI), leveraging the advantages of both inference approaches.
A stochastic approximation method
Robbins, H. and Monro, S · 1951
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A Monte Carlo implementation of the EM algorithm and the poor man’s data augmentation algorithms
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Bayesian neural networks and density networks
MacKay, D. J. C · 1995
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Training products of experts by minimizing contrastive divergence
Hinton, G. E · 2002
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On the quantitative analysis of deep belief networks
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A stochastic approximation method for inference in probabilistic graphical models
Carbonetto, P., King, M., and Hamze, F · 2009
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MCMC using Hamiltonian dynamics
Neal, R. M · 2011
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Machine Learning: A Probabilistic Perspective
Murphy, K. P · 2012
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Variational Bayesian inference with stochastic search
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Stochastic variational inference
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Stochastic backpropagation and approximate inference in deep generative models
Rezende, D. J., Mohamed, S., and Wierstra, D · 2014
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Filtering variational objectives
Maddison, C. J., Lawson, D., Tucker, G., Heess, N., Norouzi, M., Mnih, A., Doucet, A., and Teh, Y. W · 2017
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Reparameterization gradients through acceptance-rejection methods
Naesseth, C., Ruiz, F. J. R., Linderman, S., and Blei, D. M · 2017
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Learning model reparametrizations: Implicit variational inference by fitting MCMC distributions
Titsias, M. K · 2017
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Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms
Xiao, H., Rasul, K., and Vollgraf, R · 2017
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Variational rejection sampling
Grover, A., Gummadi, R., Lázaro-Gredilla, M., Schuurmans, D., and Ermon, S · 2018
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Markov chain Monte Carlo and variational inference: Bridging the gap
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Variational sequential Monte Carlo
Naesseth, C., Linderman, S. W., Ranganath, R., and Blei, D. M · 2018
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Yes, but did it work?: Evaluating variational inference
Yao, Y., Vehtari, A., Simpson, D., and Gelman, A · 2018
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Ergodic measure preserving flows
Zhang, Y., Hernández-Lobato, J. M., and Ghahramani, Z · 2018
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Auxiliary variational MCMC
Habib, R. and Barber, D · 2019
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