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Sequential Monte Carlo (SMC) is a class of algorithms that approximate high-dimensional expectations of a Markov chain.
On the theory of systematic sampling, I
Madow, W. G. & Madow, L. H. (1944) · 1944
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Poor man’s Monte Carlo
Hammersley, J. M. & Morton, K. W. (1954) · 1954
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Monte Carlo calculation of the average extension of molecular chains
Rosenbluth, M. N. & Rosenbluth, A. W. (1955) · 1955
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Monte Carlo calculations of the ground state of three-and four-body nuclei
Kalos, M. (1962) · 1962
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Monte-Carlo solution of schrödinger’s equation
Grimm, R. & Storer, R. (1971) · 1971
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Asymptotic normality for sums of dependent random variables
Dvoretzky, A. (1972) · 1972
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Dependent Central Limit Theorems and invariance principles
McLeish, D. L. (1974) · 1974
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Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence
Holland, J. H. (1975) · 1975
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Genetic algorithms for function optimization
Brindle, A. (1980) · 1980
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Martingale limit theory and its application
Hall, P. & Heyde, C. C. (1980) · 1980
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Weighted-Ensemble Brownian dynamics simulations for protein association reactions
Huber, G. A. & Kim, S. (1996) · 1996
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A basic convergence result for particle filtering
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Monte Carlo strategies in scientific computing
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A general theory of particle filters in hidden Markov models and some applications
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