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When properly tuned, Hamiltonian Monte Carlo scales to some of the most challenging high-dimensional problems at the frontiers of applied statistics, but when that tuning is suboptimal the performance leaves much to be desired.
[author] Rubin, Donald BD. B. (1981). Estimation in Parallel Randomized Experiments. Journal of Educational and Behavioral Statistics 6 377–401
1981
Earlier work this paper cites.
[author] Duane, SimonS., Kennedy, A. D.A. D., Pendleton, Brian J.B. J. and Roweth, DuncanD. (1987). Hybrid Monte Carlo. Physics Letters B 195 216 - 222
1987
Earlier work this paper cites.
[author] Gelman, AndrewA. and Rubin, Donald BD. B. (1992). Inference From Iterative Simulation Using Multiple Sequences. Statistical science 457–472
1992
Earlier work this paper cites.
[author] Robert, Christian PC. P. and Casella, GeorgeG. (1999). Monte Carlo Statistical Methods. Springer New York
1999
Earlier work this paper cites.
[author] Rubin, Donald B.D. B. (2004). Multiple imputation for nonresponse in surveys. Wiley Classics Library. Wiley-Interscience [John Wiley & Sons], Hoboken, NJ
2004
Earlier work this paper cites.
[author] Papaspiliopoulos, OmirosO., Roberts, Gareth OG. O. and Sköld, MartinM. (2007). A General Framework for the Parametrization of Hierarchical Models. Statistical Science 59–73
2007
Earlier work this paper cites.
[author] Brooks, SteveS., Gelman, AndrewA., Jones, Galin L.G. L. and Meng, Xiao-LiX.-L., eds. (2011). Handbook of Markov Chain Monte Carlo. CRC Press, New York
2011
Cited alongside, same era.
[author] Neal, R. M.R. M. (2011). MCMC Using Hamiltonian Dynamics. In Handbook of Markov Chain Monte Carlo (SteveS. Brooks, AndrewA. Gelman, Galin L.G. L. Jones and Xiao-LiX.-L. Meng, eds.) CRC Press, New York
2011
Cited alongside, same era.
Betancourt, M
2013
Cited alongside, same era.
[author] Betancourt, MichaelM., Byrne, SimonS. and Girolami, MarkM. (2014). Optimizing The Integrator Step Size for Hamiltonian Monte Carlo. ArXiv e-prints 1410.5110
2014
Cited alongside, same era.
[author] Betancourt, MichaelM., Byrne, SimonS., Livingstone, SamuelS. and Girolami, MarkM. (2014). The Geometric Foundations of Hamiltonian Monte Carlo. ArXiv e-prints 1410.5110
2014
[author] Hoffman, Matthew D.M. D. and Gelman, AndrewA. (2014). The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research 15 1593–1623
2014
Later among the works it cites.
[author] Betancourt, MichaelM. and Girolami, MarkM. (2015). Hamiltonian Monte Carlo for Hierarchical Models. In Current Trends in Bayesian Methodology with Applications (Umesh SinghU. S. Dipak K. Dey and A.A. Loganathan, eds.) Chapman & Hall/CRC Press
2015
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[author] Betancourt, MichaelM. (2016). Identifying the Optimal Integration Time in Hamiltonian Monte Carlo
2016
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[author] Livingstone, SamuelS., Betancourt, MichaelM., Byrne, SimonS. and Girolami, MarkM. (2016). On the Geometric Ergodicity of Hamiltonian Monte Carlo
2016
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Cited alongside, same era.
[author] Gelman, AndrewA., Carlin, John B.J. B., Stern, Hal S.H. S., Dunson, David B.D. B., Vehtari, AkiA. and Rubin, Donald B.D. B. (2014). Bayesian Data Analysis, third ed. Texts in Statistical Science Series. CRC Press, Boca Raton, FL
2014
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2016
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