Fetching the paper…
Reading the bibliography…
Importance Sampling methods are broadly used to approximate posterior distributions or some of their moments.
Inequalities
G. H. Hardy, J. E. Littlewood, and G. Pólya · 1952
Earlier work this paper cites.
Methods of reducing sample size in monte carlo computations
Herman Kahn and Andy W Marshall · 1953
Earlier work this paper cites.
Handbook of mathematical functions: with formulas, graphs, and mathematical tables
M. Abramowitz and I. A. Stegun · 1972
Earlier work this paper cites.
Bayesian inference in econometric models using Monte Carlo integration
J. Geweke · 1989
Earlier work this paper cites.
A note on importance sampling using standardized weights
A. Kong · 1992
Earlier work this paper cites.
Random Number Generation and Quasi-Monte Carlo Methods
H. Niederreiter · 1992
Earlier work this paper cites.
Novel approach to nonlinear and non-Gaussian Bayesian state estimation
N. Gordon, D. Salmond, and A. F. M. Smith · 1993
Earlier work this paper cites.
Sequential imputations and Bayesian missing data problems
A. Kong, J. S. Liu, and W. H. Wong · 1994
Earlier work this paper cites.
Optimally combining sampling techniques for Monte Carlo rendering
E. Veach and L. Guibas · 1995
Earlier work this paper cites.
Weighted average importance sampling and defensive mixture distributions
T. Hesterberg · 1995
Earlier work this paper cites.
Adaptive proposal distribution for random walk metropolis algorithm
H. Haario, E. Saksman, and J. Tamminen · 1999
Cited alongside, same era.
Safe and effective importance sampling
A. Owen and Y. Zhou · 2000
Cited alongside, same era.
An adaptive Metropolis algorithm
H. Haario, E. Saksman, and J. Tamminen · 2001
Cited alongside, same era.
Dynamically weighted importance sampling in Monte Carlo computation
F. Liang · 2002
Cited alongside, same era.
A theory of statistical models for monte carlo integration
A Kong, P McCullagh, X-L Meng, D Nicolae, and Z Tan · 2003
Cited alongside, same era.
Monte Carlo Statistical Methods
C. P. Robert and G. Casella · 2004
Cited alongside, same era.
Comparison of resampling schemes for particle filtering
R. Douc and O. Cappé · 2005
Later among the works it cites.
Adaptive importance sampling in general mixture classes
O. Cappé, R. Douc, A. Guillin, J. M. Marin, and C. P. Robert · 2008
Later among the works it cites.
Adaptive multiple importance sampling
J. M. Cornuet, J. M. Marin, A. Mira, and C. P. Robert · 2012
Later among the works it cites.
Monte Carlo theory, methods and examples
A. Owen · 2013
Later among the works it cites.
Optimal mixture weights in multiple importance sampling
H. Y. He and A. B. Owen · 2014
Later among the works it cites.
An adaptive population importance sampler: Learning from the uncertanity
L. Martino, V. Elvira, D. Luengo, and J. Corander · 2015
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
J. S. Liu · 2004
Cited alongside, same era.
On a likelihood approach for monte carlo integration
Z. Tan · 2004
Cited alongside, same era.
Population Monte Carlo
O. Cappé, A. Guillin, J. M. Marin, and C. P. Robert · 2004
Cited alongside, same era.
P. W. Gwanyama · 2004
Cited alongside, same era.
Efficient multiple importance sampling estimators
V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo
Cited in the paper.
Convergence of adaptive mixtures of importance sampling schemes
G.R. Douc, J.M. Marin, and C. Robert
Cited in the paper.
Heretical multiple importance sampling
V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo · 2016
Closest in time.
Layered adaptive importance sampling
L. Martino, V. Elvira, D. Luengo, and J. Corander · 2017
Closest in time.
Improving Population Monte Carlo: Alternative weighting and resampling schemes
V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo · 2017
Closest in time.
Adaptive importance sampling: The past, the present, and the future
M. F. Bugallo, V. Elvira, L. Martino, D. Luengo, J. Míguez, and P. M. Djuric · 2017
Closest in time.