Feynman-Kac Formulae: Genealogical and Interacting Particle Systems with Applications

By Pierre Del Moral. 2004

1,147 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b76051add4f2ffb97d28be2e146e3a66a7ac5bea

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Citations in the corpus

Nonequilibrium Markov Processes Conditioned on Large Deviations (2014, background): “A further link with rare event sampling is established in that the semi-group or propagator of Yt is deeply related to Feynman–Kac functionals, which underlie cloning [29–31] and genealogical [32] methods also used for sampling rare events.”
Sequential Monte Carlo with Highly Informative Observations (2014, methodology): “Because SMC methods are a particular case of mean field particle methods [11], these ancestral D ow nl oa de d 12 /0 3/ 19 to 1 63 .”
Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach (2013, background): “Within-model simulations are simpler, but generalisations of the harmonic mean estimator (Gelfand and Dey, 1994) which are widely used in this setting require careful design to ensure finite variances and, convergence assessment can be di fficult. Simulations on the whole model spaces are often di f”
Robust filtering: Correlated noise and multidimensional observation (2012, methodology): “In this case the filtering problem is well understood and has been studied in many works, including the monograph [15] and the articles [16–18].”
Error Bounds and Normalising Constants for Sequential Monte Carlo Samplers in High Dimensions (2014, methodology): “The normalising constant in SMC methods has been well studied; see [7] and [9].”
An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo (2007, background): “Equation (36) is referred to by [44] as a (discretetime) Feynman-Kac system of probability distributions.”
Biips: Software for Bayesian Inference with Interacting Particle Systems (2014, methodology): “The introduction of the monograph of Del Moral (2013) provides early references on this class of algorithms and an extensive list of application domains.”
Genealogical particle analysis of rare events (2005, methodology): “ccurrence of the rare events by using importance sampling (IS) [16, 24]. More reﬁned sampling importance resampling (SIR) and closely related sequential Monte Carlo methods (SMC) can also be found in [4, 10]. In Received May 2004; revised April 2005. AMS 2000 subject classiﬁcations. 65C35, 65C20, 60”
Quasilimiting behavior for one-dimensional diffusions with killing (2010, background): “…(1966), Högnäs (1997), Haridas and Tuljapurkar (2005), Cattiaux et al. (2009), demography: Steinsaltz and Evans (2004), Le Bras (1976), Li and Anderson (2009), medicine: Manton and Stallard (1988), Yashin et al. (2007) and statistics: Aalen (1995), Aalen and Gjessing (2003), Del Moral (2004)].”
Particle Belief Propagation (2009, methodology): “Considerable work has gone into analyzing particle representations on Markov chains (particle filtering); see for example Del Moral (2004) for details.”
Beyond Gaussian Statistical Modeling in Geophysical Data Assimilation (2010, background): “Finally, the authors thank M. Krysta and L. Delle Monache for their careful reading of the manuscript and for their useful comments.”