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A number of problems in a variety of fields are characterised by target distributions with a multimodal structure in which the presence of several isolated local maxima dramatically reduces the efficiency of Markov Chain Monte Carlo sampling algorithms.
Monte Carlo sampling methods using Markov chains and their applications
Hastings, W. (1970) · 1970
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Optimum Monte Carlo sampling using Makov chains
Peskun, P. H. (1973) · 1973
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Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D. and Vecchi, M. P. (1983) · 1983
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Monte Carlo methods in statistical mechanics: foundations and new algorithms
Sokal, A. D. (1989) · 1989
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Markov chain Monte Carlo maximum likelihood
Geyer, C. J. (1991) · 1991
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Simulated Tempering: a New Monte Carlo Scheme
Marinari, E. and Parisi, G. (1992) · 1992
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Annealing Markov Chain Monte Carlo with applications to Ancestral Inference
Geyer, C. J. and Thompson, E. A. (1995) · 1995
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Markov Chain Monte Carlo in practice
Gilks, W., Richardson and S., Spiegelhalter, D. (1995) · 1995
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Reversible jump MCMC computation and Bayesian model determination
Green, P. J. (1995) · 1995
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Efficient Metropolis Jumping Rules
Gelman, A. et al · 1996
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Markov Chain Monte Carlo: Stochastic Simulation of Bayesian Inference
Gamerman, D. (1997) · 1997
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Bender, P. and Danzmann, K. and the LISA Study Team (1998) · 1998
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Angular resolution of the LISA gravitational wave detector
Cutler, C. (1998) · 1998
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Some adaptive Monte Carlo methods for Bayesian inference
Tierney, L. and Mira, A. (1999) · 1999
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Parallel chains, delayed rejection and reversible jump MCMC for object recognition
Harkness, M. A. and Green, P. J. (2000) · 2000
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Delayed rejection in reversible jump Metropolis-Hastings
Green, P. J. and Mira, A. (2001) · 2001
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On Metropolis-Hastings algorithms with delayed rejection
Mira, A. (2001) · 2001
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DRAM: Efficient adaptive MCMC
Haario, H., Laine, M., Mira, A. and Saksman, E. (2006) · 2006
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Tests of Bayesian Model Selection Techniques for Gravitational Wave Astronomy
Cornish, N. J. and Littenberg T. B. (2007) · 2007
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The search for massive black hole binaries with LISA
Cornish, N. J. and Porter, E. K. (2007) · 2007
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Solution to the galactic foreground problem for LISA
Crowder, J. and Cornish, N. J. (2007) · 2007
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The Mock LISA Data Challenges: from Challenge 1B to Challenge 3
Babak, S. et al · 2008
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Detection Strategies for Extreme Mass Ratio Inspirals
Cornish, N. J. (2008) · 2008
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Ordering and improving the performance of Monte Carlo Markov Chains
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IID sampling with self-avoiding particle filters: the pinball sampler
Robert C. P. and Mengersen, L. (2003) · 2003
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Improving the acceptance rate of reversible jump MCMC proposals
Al-Awadhi, F., Hurn, M. and Jennison, C. (2004) · 2004
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Estimating the parameters of gravitational waves from neutron stars using an adaptive MCMC method
Umstätter, R. et al · 2004
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Adaptive MCMC methods for inference on affine stochastic volatility models with jumps
Raggi, D. (2005) · 2005
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A constrained Metropolis-Hastings search for EMRIs in the Mock LISA Data Challenge 1B
Gair, J. R. et al · 2008
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Markov chain Monte Carlo searches for Galactic binaries in Mock LISA Data Challenge 1B data sets
Trias, M., Vecchio, A. and Veitch, J. (2008) · 2008
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An algorithm for detection of extreme mass ratio inspirals in LISA data
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A Bayesian Approach to the Detection Problem in Gravitational Wave Astronomy
Littenberg, T. B. and Cornish, N. J. (2009) · 2009
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