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Markov chain Monte Carlo

Known as: Monte Carlo markov chain, Markov Chain Monte Carlo Simulations, Markov clustering 
In statistics, Markov chain Monte Carlo (MCMC) methods are a class of algorithms for sampling from a probability distribution based on constructing a… Expand
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Highly Cited
2008
Highly Cited
2008
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such… Expand
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Highly Cited
2006
Highly Cited
2006
Differential Evolution (DE) is a simple genetic algorithm for numerical optimization in real parameter spaces. In a statistical… Expand
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Highly Cited
2002
Highly Cited
2002
This paper is about estimating the parameters of the exponential random graph model, also known as the p∗ model, using… Expand
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Highly Cited
2002
Highly Cited
2002
This paper is concerned with simulation-based inference in generalized models of stochastic volatility defined by heavy-tailed… Expand
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Highly Cited
2002
Highly Cited
2002
In a full Bayesian probabilistic framework for "robust" system identification, structural response predictions and performance… Expand
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Highly Cited
1998
Highly Cited
1998
Abstract Markov chain Monte Carlo (MCMC) methods make possible the use of flexible Bayesian models that would otherwise be… Expand
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Highly Cited
1997
Highly Cited
1997
INTRODUCING MARKOV CHAIN MONTE CARLO Introduction The Problem Markov Chain Monte Carlo Implementation Discussion HEPATITIS B: A… Expand
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Highly Cited
1997
Highly Cited
1997
Stochastic simulation Bayesian inference approximate methods of inference Markov chains Gibbs sampling Metropolis-Hastings… Expand
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Highly Cited
1996
Highly Cited
1996
 
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Highly Cited
1995
Highly Cited
1995
 
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