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Hamiltonian Monte Carlo (HMC) and related algorithms have become routinely used in Bayesian computation.
“Equation of State Calculations by Fast Computing Machines.”
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E. (1953) · 1953
Earlier work this paper cites.
“Hybrid Monte Carlo.”
Duane, S., Kennedy, A., Pendleton, B. J., and Roweth, D. (1987) · 1987
Earlier work this paper cites.
“Acceptances and autocorrelations in hybrid Monte Carlo.”
Kennedy, A. and Pendleton, B. (1991) · 1991
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“An Improved Acceptance Procedure for the Hybrid Monte Carlo Algorithm.”
Neal, R. M. (1994) · 1994
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Bayesian Learning for Neural Networks
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Earlier work this paper cites.
Foundations of Modern Probability
Kallenberg, O. (2002) · 2002
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“Speed-up of Monte Carlo simulations by sampling of rejected states.”
Frenkel, D. (2004) · 2004
Earlier work this paper cites.
“Using all Metropolis-Hastings proposals to estimate mean values.”
Tjelmeland, H. (2004) · 2004
Earlier work this paper cites.
“A tutorial on adaptive MCMC.”
Andrieu, C. and Thoms, J. (2008) · 2008
Earlier work this paper cites.
“MCMC using Hamiltonian Dynamics.”
— (2010) · 2010
Earlier work this paper cites.
Handbook of Markov Chain Monte Carlo
Brooks, S., Gelman, A., Jones, G., and Meng, X.-L. (eds.) (2011) · 2011
Earlier work this paper cites.
“Riemann manifold Langevin and Hamiltonian Monte Carlo methods.”
Girolami, M. and Calderhead, B. (2011) · 2011
Cited alongside, same era.
“Model choice using reversible jump Markov chain Monte Carlo.”
Hastie, D. I. and Green, P. J. (2012) · 2012
Cited alongside, same era.
“Optimal tuning of the hybrid Monte Carlo algorithm.”
Beskos, A., Pillai, N., Roberts, G., Sanz-Serna, J.-M., and Stuart, A. (2013) · 2013
Cited alongside, same era.
Bayesian Data Analysis
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013) · 2013
Cited alongside, same era.
“Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions.”
Pakman, A. and Paninski, L. (2013) · 2013
Cited alongside, same era.
“Adaptive Hamiltonian and Riemann manifold Monte Carlo samplers.”
Wang, Z., Mohamed, S., and de Freitas, N. (2013) · 2013
“Exact Hamiltonian Monte Carlo for Truncated Multivariate Gaussians.”
— (2014) · 2014
Later among the works it cites.
“Split Hamiltonian Monte Carlo.”
Shahbaba, B., Lan, S., Johnson, W. O., and Neal, R. M. (2014) · 2014
Later among the works it cites.
“Locally weighted Markov chain Monte Carlo.”
Bernton, E., Yang, S., Chen, Y., Shephard, N., and Liu, J. S. (2015) · 2015
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Stan Modeling Language Users Guide and Reference Manual, Version 2.9.0
Stan Development Team (2015) · 2015
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“On the Geometric Ergodicity of Hamiltonian Monte Carlo.”
Livingstone, S., Betancourt, M., Byrne, S., and Girolami, M. (2016) · 2016
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“Relativistic Monte Carlo.”
Lu, X., Perrone, V., Hasenclever, L., Teh, Y. W., and Vollmer, S. J. (2016) · 2016
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Cited alongside, same era.
“A general construction for parallelizing Metropolis-Hastings algorithms.”
Calderhead, B. (2014) · 2014
Cited alongside, same era.
“Compressible generalized hybrid Monte Carlo.”
Fang, Y., Sanz-Serna, J. M., and Skeel, R. D. (2014) · 2014
Cited alongside, same era.
“The No-U-turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo.”
Hoffman, M. D. and Gelman, A. (2014) · 2014
Cited alongside, same era.
Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan
Kruschke, J. (2014) · 2014
Cited alongside, same era.
“Spherical Hamiltonian Monte Carlo for Constrained Target Distributions.”
Lan, S., Zhou, B., and Shahbaba, B. (2014) · 2014
Cited alongside, same era.
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“Faster estimation of Bayesian models in ecology using Hamiltonian Monte Carlo.”
Monnahan, C. C., Thorson, J. T., and Branch, T. A. (2016) · 2016
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“Probabilistic programming in Python using PyMC3.”
Salvatier, J., Wiecki, T. V., and Fonnesbeck, C. (2016) · 2016
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“Towards Unifying Hamiltonian Monte Carlo and Slice Sampling.”
Zhang, Y., Wang, X., Chen, C., Henao, R., Fan, K., and Carin, L. (2016) · 2016
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“Kinetic energy choice in Hamiltonian/hybrid Monte Carlo.”
Livingstone, S., Faulkner, M. F., and Roberts, G. O. (2017) · 2017
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“Rapid mixing of Hamiltonian Monte Carlo on strongly log-concave distributions.”
Mangoubi, O. and Smith, A. (2017) · 2017
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