A new strategy for effective learning in population Monte Carlo sampling

2016 50th Asilomar Conference on Signals, Systems and Computers ◽

10.1109/acssc.2016.7869636 ◽

2016 ◽

Author(s):

Monica F. Bugallo ◽

Victor Elvira ◽

Luca Martino

Keyword(s):

Monte Carlo ◽

Monte Carlo Sampling ◽

Effective Learning ◽

Population Monte Carlo ◽

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Enhanced Mixture Population Monte Carlo Via Stochastic Optimization and Markov Chain Monte Carlo Sampling

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp40776.2020.9053410 ◽

2020 ◽

Author(s):

Yousef El-Laham ◽

Petar M. Djuric ◽

Monica F. Bugallo

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Stochastic Optimization ◽

Monte Carlo Sampling ◽

Population Monte Carlo

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Estimation of posterior distributions with population Monte Carlo sampling and graphical modeling

2012 IEEE Statistical Signal Processing Workshop (SSP) ◽

10.1109/ssp.2012.6319677 ◽

2012 ◽

Author(s):

Petar M. Djuric ◽

Cagla Tasdemir

Keyword(s):

Monte Carlo ◽

Monte Carlo Sampling ◽

Posterior Distributions ◽

Graphical Modeling ◽

Population Monte Carlo

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Estimation of multimodal posterior distributions of chirp parameters with population Monte Carlo sampling

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp.2012.6288760 ◽

2012 ◽

Author(s):

Bingxin Shen ◽

Monica F. Bugallo ◽

Petar M. Djuric

Keyword(s):

Monte Carlo ◽

Monte Carlo Sampling ◽

Posterior Distributions ◽

Population Monte Carlo

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Bayesian inference, Monte Carlo sampling and operational risk

The Journal of Operational Risk ◽

10.21314/jop.2006.014 ◽

2006 ◽

Vol 1 (3) ◽

pp. 27-50 ◽

Author(s):

G Peters ◽

S Sisson

Keyword(s):

Monte Carlo ◽

Bayesian Inference ◽

Operational Risk ◽

Monte Carlo Sampling

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A Monte Carlo Sampling Method of Amino Acid Sequences Adaptable to Given Main-Chain Atoms in the Proteins

The Journal of Biochemistry ◽

10.1093/jb/mvj184 ◽

2006 ◽

Vol 140 (4) ◽

pp. 543-552

Author(s):

Koji Ogata ◽

Kenji Soejima ◽

Junichi Higo

Keyword(s):

Monte Carlo ◽

Sampling Method ◽

Monte Carlo Sampling ◽

Amino Acid Sequences

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Probabilistic Optimal Power Flow With Correlated Wind Power Uncertainty via Markov Chain Quasi-Monte-Carlo Sampling

IEEE Transactions on Industrial Informatics ◽

10.1109/tii.2019.2928054 ◽

2019 ◽

Vol 15 (11) ◽

pp. 6058-6069 ◽

Author(s):

Weigao Sun ◽

Mohsen Zamani ◽

Hai-Tao Zhang ◽

Yuanzheng Li

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Optimal Power Flow ◽

Monte Carlo Sampling ◽

Quasi Monte Carlo ◽

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Monte Carlo sampling of solutions to inverse problems

International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts ◽

10.1016/0148-9062(96)80050-7 ◽

1996 ◽

Vol 33 (5) ◽

pp. A219

Keyword(s):

Monte Carlo ◽

Inverse Problems ◽

Monte Carlo Sampling

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Locating stationary paths in functional integrals: An optimization method utilizing the stationary phase Monte Carlo sampling function

The Journal of Chemical Physics ◽

10.1063/1.455868 ◽

1989 ◽

Vol 90 (6) ◽

pp. 3181-3191 ◽

Author(s):

Thomas L. Beck ◽

J. D. Doll ◽

David L. Freeman

Keyword(s):

Monte Carlo ◽

Stationary Phase ◽

Optimization Method ◽

Monte Carlo Sampling ◽

Functional Integrals ◽

Sampling Function

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A phase‐space theory and Monte Carlo sampling method for studying nonadiabatic unimolecular reactions

The Journal of Chemical Physics ◽

10.1063/1.462092 ◽

1992 ◽

Vol 96 (3) ◽

pp. 1911-1918 ◽

Author(s):

Alison J. Marks ◽

Donald L. Thompson

Keyword(s):

Monte Carlo ◽

Phase Space ◽

Sampling Method ◽

Monte Carlo Sampling ◽

Space Theory ◽

Unimolecular Reactions ◽

Phase Space Theory

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Monte Carlo Sampling with Hierarchical Move Sets: POSH Monte Carlo

Journal of Chemical Theory and Computation ◽

10.1021/ct8005166 ◽

2009 ◽

Vol 5 (8) ◽

pp. 1968-1984 ◽

Author(s):

Jerome Nilmeier ◽

Matthew P. Jacobson

Keyword(s):

Monte Carlo ◽

Monte Carlo Sampling

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