Keyword

proposal distribution

Description: A probability distribution from which candidate values or states are sampled in sequential Monte Carlo and particle filtering methods.

Primary topic: Markov Chains and Monte Carlo Methods (32%)

OpenAlex ID: keywords/proposal-distribution

An Adaptive Metropolis Algorithm

2001 · Heikki Haario, Eero Saksman, et al. · Bernoulli · 2,636

Particle Markov Chain Monte Carlo Methods

2010 · Christophe Andrieu, Arnaud Doucet, et al. · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1,974

A Boosted Particle Filter: Multitarget Detection and Tracking

2004 · Kenji Okuma, Ali Taleghani, et al. · Lecture notes in computer science · 1,022

M arkov Chain M onte C arlo

2005 · W. R. Gilks · Encyclopedia of Biostatistics · 711

Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training

2020 · Hongkai Zhang, Hong Chang, et al. · Lecture notes in computer science · 700

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Optimal Scaling of Discrete Approximations to Langevin Diffusions

1998 · Gareth O. Roberts, Jeffrey S. Rosenthal · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 632

Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods

1999 · Bob Mau, Michael A. Newton, et al. · Biometrics · 541

Data Fusion for Visual Tracking With Particles

2004 · P. Perez, J. Vermaak, et al. · Proceedings of the IEEE · 470

A Split-Merge Markov chain Monte Carlo Procedure for the Dirichlet Process Mixture Model

2004 · Sonia Jain, Radford M Neal · Journal of Computational and Graphical Statistics · 451

Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects

2008 · Martina Morris, Mark S. Handcock, et al. · Journal of Statistical Software · 407

Better proposal distributions: object tracking using unscented particle filter

2005 · Yong Rui, Yunqiang Chen · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 283

On the Relationship Between Markov chain Monte Carlo Methods for Model Uncertainty

2001 · Simon J Godsill · Journal of Computational and Graphical Statistics · 281

Improving the estimation of parameter uncertainty distributions in nonlinear mixed effects models using sampling importance resampling

2016 · Anne-Gaëlle Dosne, Martin Bergstrand, et al. · Journal of Pharmacokinetics and Pharmacodynamics · 251

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Monte Carlo Localization with Mixture Proposal Distribution

2000 · Sebastian Thrun, Dieter Fox, et al. · 191

Phylogenetic Inference for Binary Data on Dendograms Using Markov Chain Monte Carlo

1997 · Bob Mau, Michael A. Newton · Journal of Computational and Graphical Statistics · 177

A general purpose sampling algorithm for continuous distributions (the t-walk)

2010 · J. Andrés Christen, Colin Fox · Bayesian Analysis · 174

DREAM (D) : an adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems

2011 · J. A. Vrugt, C. J. F. Ter Braak · Hydrology and earth system sciences · 167

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Generalized Multiple Importance Sampling

2019 · Víctor Elvira, Luca Martino, et al. · Statistical Science · 142

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Efficient Block Sampling Strategies for Sequential Monte Carlo Methods

2006 · Arnaud Doucet, Mark Briers, et al. · Journal of Computational and Graphical Statistics · 141

GalPaK3D: A BAYESIAN PARAMETRIC TOOL FOR EXTRACTING MORPHOKINEMATICS OF GALAXIES FROM 3D DATA

2015 · N. Bouché, H. Carfantan, et al. · The Astronomical Journal · 139

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Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association

2007 · Qian Yu, Gerard Medioni, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 132

A New Evolutionary Particle Filter for the Prevention of Sample Impoverishment

2009 · Seongkeun Park, Jae Pil Hwang, et al. · IEEE Transactions on Evolutionary Computation · 126

Data assimilation with the weighted ensemble Kalman filter

2010 · Nicolas Papadakis, Etienne Mémin, et al. · Tellus A Dynamic Meteorology and Oceanography · 117

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An Efficient Two-Stage Sampling Method for Uncertainty Quantification in History Matching Geological Models

2008 · Xianlin Ma, Mishal Al-Harbi, et al. · SPE Journal · 115

Layered adaptive importance sampling

2016 · L. Martino, V. Elvira, et al. · Statistics and Computing · 105

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Works count: 928

Citation count: 18,200