5 Using Hamiltonian Dynamics

[1]  Radford M. Neal.  Probabilistic Inference Using Markov Chain Monte Carlo Methods , 2011 .

[2]  Ben Calderhead,et al.  Riemannian Manifold Hamiltonian Monte Carlo , 2009, 0907.1100.

[3]  Mikkel N. Schmidt.  Function factorization using warped Gaussian processes , 2009, ICML '09.

[4]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[5]  Christophe Andrieu,et al.  A tutorial on adaptive MCMC , 2008, Stat. Comput..

[6]  David J. Earl,et al.  Parallel tempering: theory, applications, and new perspectives. , 2005, Physical chemistry chemical physics : PCCP.

[7]  Radford M. Neal.  The Short-Cut Metropolis Method , 2005, math/0508060.

[8]  Scott S. Hampton,et al.  Shadow hybrid Monte Carlo: an efficient propagator in phase space of macromolecules , 2004 .

[9]  A. P. Dawid,et al.  Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals , 2003 .

[10]  Jun S. Liu,et al.  Multipoint metropolis method with application to hybrid Monte Carlo , 2001 .

[11]  A. Kennedy,et al.  Cost of the Generalised Hybrid Monte Carlo Algorithm for Free Field Theory , 2000, hep-lat/0008020.

[12]  Radford M. Neal.  Annealed importance sampling , 1998, Stat. Comput..

[13]  Jun S. Liu,et al.  Monte Carlo strategies in scientific computing , 2001 .

[14]  Kiam Choo.  Learning hyperparameters for neural network models using Hamiltonian dynamics , 2000 .

[15]  H. Ishwaran.  Applications of Hybrid Monte Carlo to Bayesian Generalized Linear Models: Quasicomplete Separation and Neural Networks , 1999 .

[16]  J. Rosenthal,et al.  Optimal scaling of discrete approximations to Langevin diffusions , 1998 .

[17]  A. Gelman,et al.  Weak convergence and optimal scaling of random walk Metropolis algorithms , 1997 .

[18]  Pal Rujan,et al.  Playing Billiards in Version Space , 1997, Neural Computation.

[19]  Radford M. Neal.  Sampling from multimodal distributions using tempered transitions , 1996, Stat. Comput..

[20]  R. Tweedie,et al.  Exponential convergence of Langevin distributions and their discrete approximations , 1996 .

[21]  Berend Smit,et al.  Understanding molecular simulation: from algorithms to applications , 1996 .

[22]  Geoffrey E. Hinton,et al.  Bayesian Learning for Neural Networks , 1995 .

[23]  Michael I. Miller,et al.  REPRESENTATIONS OF KNOWLEDGE IN COMPLEX SYSTEMS , 1994 .

[24]  S. Caracciolo,et al.  A general limitation on Monte Carlo algorithms of the Metropolis type. , 1993, Physical review letters.

[25]  Radford M. Neal.  An improved acceptance procedure for the hybrid Monte Carlo algorithm , 1992, hep-lat/9208011.

[26]  J. Sexton,et al.  Hamiltonian evolution for the hybrid Monte Carlo algorithm , 1992 .

[27]  G. Parisi,et al.  Simulated tempering: a new Monte Carlo scheme , 1992, hep-lat/9205018.

[28]  R. McLachlan,et al.  The accuracy of symplectic integrators , 1992 .

[29]  A. Horowitz.  A generalized guided Monte Carlo algorithm , 1991 .

[30]  A. Kennedy,et al.  Acceptances and autocorrelations in hybrid Monte Carlo , 1991 .

[31]  Sourendu Gupta,et al.  The acceptance probability in the hybrid Monte Carlo method , 1990 .

[32]  A. Kennedy.  The theory of hybrid stochastic algorithms , 1990 .

[33]  Paul B. Mackenze.  An Improved Hybrid Monte Carlo Method , 1989 .

[34]  Creutz,et al.  Higher-order hybrid Monte Carlo algorithms. , 1989, Physical review letters.

[35]  Creutz.  Global Monte Carlo algorithms for many-fermion systems. , 1988, Physical review. D, Particles and fields.

[36]  A. Kennedy,et al.  Hybrid Monte Carlo , 1987 .

[37]  J. Doll,et al.  Brownian dynamics as smart Monte Carlo simulation , 1978 .

[38]  Charles H. Bennett,et al.  Mass tensor molecular dynamics , 1975 .

[39]  V. Arnold.  Mathematical Methods of Classical Mechanics , 1974 .

[40]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[41]  B. Alder,et al.  Studies in Molecular Dynamics. I. General Method , 1959 .

[42]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.