Computational Methods for a Class of Network Models

Keywords

Markov chain Monte Carlo, Particle filter, Computer science, Algorithm, Likelihood function

References

• Feynman-Kac Formulae: Genealogical and Interacting Particle Systems with ApplicationsPierre Del Moral — 2004
• Particle Markov chain Monte Carlo methodsChristophe Andrieu, Arnaud Doucet, Roman Holenstein — 2010
• Efficient Bayesian Inference for Switching State-Space Models using Discrete Particle Markov Chain Monte Carlo MethodsNick Whiteley, Christophe Andrieu, Arnaud Doucet — 2010
• Monte Carlo Statistical MethodsHoon Kim, Christian P. Robert, George Casella — 2004
• Adaptive importance sampling for network growth modelsAdam Guetz, Susan Holmes — 2011
• A nonasymptotic theorem for unnormalized Feynman-Kac particle modelsFrédéric Cérou, Pierre Del Moral, Arnaud Guyader — 2011
• A likelihood approach to analysis of network dataCarsten Wiuf, Markus Brameier, Oskar Hagberg — 2006
• Path storage in the particle filterPierre E. Jacob, Lawrence M. Murray, Sylvain Rubenthaler — 2013
• Efficient Block Sampling Strategies for Sequential Monte Carlo MethodsArnaud Doucet, Mark Briers, Stéphane Sénécal — 2006
• The pseudo-marginal approach for efficient Monte Carlo computationsChristophe Andrieu, Gareth O. Roberts — 2009
• On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methodsAnthony Lee, Christopher Yau, Michael B. Giles — 2009
• Simulating Probability Distributions in the CoalescentRobert Griffiths, Simon Tavaré — 1994
• The time machine: a simulation approach for stochastic treesAjay Jasra, Maria De Iorio, Marc Chadeau-Hyam — 2010
• Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimatorArnaud Doucet, M. Pitt, George Deligiannidis — 2012
• Linear Variance Bounds for Particle Approximations of Time-Homogeneous Feynman-Kac FormulaeNick Whiteley, Nikolas Kantas, Ajay Jasra — 2011
• Sequential Monte Carlo samplersPierre Del Moral, Arnaud Doucet, Ajay Jasra — 2002
• On the stability of sequential Monte Carlo methods in high dimensionsAlexandros Beskos, Dan Crisan, Ajay Jasra — 2011
• A non asymptotic variance theorem for unnormalized Feynman-Kac particle modelsFrédéric Cérou, Pierre Del Moral, Arnaud Guyader — 2008
• On adaptive resampling strategies for sequential Monte Carlo methodsPierre Del Moral, Arnaud Doucet, Ajay Jasra — 2012
• On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methodsAnthony Lee, Christopher Yau, Michael B. Giles — 2009

Cited by

• A Stable Particle Filter in High-DimensionsAlex Beskos, Dan Crisan, Ajay Jasra — 2014
• Path storage in the particle filterPierre E. Jacob, Lawrence M. Murray, Sylvain Rubenthaler — 2013
• Monte Carlo algorithms for computing α α-permanentsJunshan Wang, Ajay Jasra — 2016
• A Bayesian mixture of lasso regressions with t-errorsAlberto Cozzini, Ajay Jasra, Giovanni Montana — 2014
• Bayesian Inference for Duplication–Mutation with Complementarity Network ModelsAjay Jasra, Adam Persing, Alexandros Beskos — 2015
• Random‐walk models of network formation and sequential Monte Carlo methods for graphsBenjamin Bloem-Reddy, Peter Orbanz — 2016
• Transcriptome analysis of green and purple fruited pepper provides insight into novel regulatory genes in anthocyanin biosynthesisHuaqiang Tan, Liping Li, Manman Tie — 2024
• Phase Transition in the Recoverability of Network HistoryJean-Gabriel Young, Guillaume St-Onge, Edward Laurence — 2019
• Path storage in the particle filterJacob, Pierre E., Murray, Lawrence, Rubenthaler, Sylvain — 2013

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