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Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for defining distant proposals with high acceptance probabilities in a Metropolis-Hastings framework, enabling more efficient exploration of the state space than standard random-walk proposals.
On the Theory of the Brownian Motion II
Wang, M.C. and Uhlenbeck, G.E · 1945
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A stochastic approximation method
Robbins, H. and Monro, S · 1951
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Hybrid Monte Carlo
Duane, S., Kennedy, A.D., Pendleton, B.J., and Roweth, D · 1987
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A generalized guided Monte Carlo algorithm
Horowitz, A.M · 1991
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Bayesian learning via stochastic dynamics
Neal, R.M · 1993
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Yin, L. and Ao, P · 2006
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Markov Chains and Mixing Times
Levin, D.A., Peres, Y., and Wilmer, E.L · 2008
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Robust stochastic approximation approach to stochastic programming
Nemirovski, A., Juditsky, A., Lan, G., and Shapiro, A · 2009
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MCMC using Hamiltonian dynamics
Neal, R.M · 2010
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Riemann manifold Langevin and Hamiltonian Monte Carlo methods
Girolami, M. and Calderhead, B · 2011
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The No-U-Turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo
Hoffman, M.D. and Gelman, A · 2011
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Bayesian learning via stochastic gradient Langevin dynamics
Welling, M. and Teh, Y.W · 2011
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Bayesian posterior sampling via stochastic gradient Fisher scoring
Ahn, S., Korattikara, A., and Welling, M · 2012
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Stochastic variational inference
Hoffman, M.D., Blei, D. M., Wang, C., and Paisley, J · 2013
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Stochastic gradient Riemannian Langevin dynamics on the probability simplex
Patterson, S. and Teh, Y.W · 2013
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On the importance of initialization and momentum in deep learning
Sutskever, I., Martens, J., Dahl, G. E., and Hinton, G. E · 2013
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Adaptive Hamiltonian and Riemann manifold Monte Carlo
Wang, Z., Mohamed, S., and Nando, D · 2013
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Towards scaling up Markov chain Monte Carlo: An adaptive subsampling approach
Bardenet, R., Doucet, A., and Holmes, C · 2014
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Austerity in MCMC land: Cutting the Metropolis-Hastings budget
Korattikara, A., Chen, Y., and Welling, M · 2014
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Relation of a new interpretation of stochastic differential equations to Ito process
Shi, J., Chen, T., Yuan, R., Yuan, B., and Ao, P · 2012
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Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Salakhutdinov, R. and Mnih, A
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Probabilistic matrix factorization
Salakhutdinov, R. and Mnih, A
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