Litt´ erature
481
34. Del Moral P., Miclo L. Self Interacting Markov chains. Stochastic Analysis
and Applications, vol. 24, no. 3, pp. 615–660 (2006).
35. Del Moral P., Miclo L. On convergence of chains with time empirical selfinteractions. Proc. Royal Soc. Lond. A., vol. 460, pp. 325–346 (2003).
36. P. Del Moral. Feynman-Kac formulae. Genealogical and interacting particle
systems. Springer-Verlag : New York (2004).
37. P. Del Moral. Mean field simulation for Monte Carlo integration. Chapman
& Hall/CRC Press. Monographs on Statistics and Applied Probability (2013).
38. P. Del Moral. Non Linear Filtering : Interacting Particle Solution. Markov
Processes and Related Fields, Volume 2 Number 4, 555–580 (1996).
39. P. Del Moral.
Measure-valued processes and interacting particle
systems. Application to nonlinear filtering problems. Ann. Appl. Probab., 8(2) :438–495 (1998).
40. P. Del Moral,, A. Doucet, & A. Jasra. Sequential Monte Carlo
samplers. J. R. Statist. Soc. B, 68, 411–436 (2006).
41. P. Del Moral,, A. Doucet, & A. Jasra. An Adaptive Sequential Monte Carlo
Method for Approximate Bayesian Computation Statistics and Computing, vol.
22, no. 5, pp. 1009–1020 (2012).
42. P. Del Moral, P. Hu, L. Wu. On the concentration properties of Interacting
particle processes. Foundations and Trends in Machine Learning, vol. 3, nos.
3–4, pp. 225–389 (2012).
43. P. Del Moral, A. Doucet, and A. Jasra. On adaptive resampling procedures for sequential Monte Carlo Bernoulli, vol. 18, no. 1, pp. 252-278 (2012).
44. P. Del Moral,, A. Doucet, & G. W. Peters. Sharp Propagations of
Chaos Estimates for Feynman-Kac particle Models Probability Theory and
its Applications SIAM, vol. 51, no. 3 (2006).
45. P. Del Moral, A. Doucet, and S. S. Singh. A Backward Particle Interpretation of Feynman-Kac Formulae. ESAIM M2AN, vol 44, no. 5, pp. 947–976
(2010).
46. P. Del Moral, A. Doucet, and S. S. Singh. Forward Smoothing Using Sequential Monte Carlo Technical Report 638. Cambridge University Engineering
Department (2010).
47. P. Del Moral, A. Doucet, and S. S. Singh. Uniform stability of a particle approximation of the optimal filter derivative. Technical Report CUED/FINFENG/TR 668. Cambridge University Engineering Department (2011).
48. P. Del Moral and J. Garnier. Genealogical particle analysis of rare
events. Ann. Appl. Probab., 15(4) :2496–2534 (2005).
49. P. Del Moral and J. Garnier. Simulations of rare events in fiber
optics by interacting particle systems. Optics Communications, Vol.
257, pp. 205-214 (2006).
50. P. Del Moral, J. Jacod. and P. Protter, The Monte-Carlo Method for
filtering with discrete-time observations, Probability Theory and Related Fields,
vol. 120, pp. 346–368, (2001).
481
34. Del Moral P., Miclo L. Self Interacting Markov chains. Stochastic Analysis
and Applications, vol. 24, no. 3, pp. 615–660 (2006).
35. Del Moral P., Miclo L. On convergence of chains with time empirical selfinteractions. Proc. Royal Soc. Lond. A., vol. 460, pp. 325–346 (2003).
36. P. Del Moral. Feynman-Kac formulae. Genealogical and interacting particle
systems. Springer-Verlag : New York (2004).
37. P. Del Moral. Mean field simulation for Monte Carlo integration. Chapman
& Hall/CRC Press. Monographs on Statistics and Applied Probability (2013).
38. P. Del Moral. Non Linear Filtering : Interacting Particle Solution. Markov
Processes and Related Fields, Volume 2 Number 4, 555–580 (1996).
39. P. Del Moral.
Measure-valued processes and interacting particle
systems. Application to nonlinear filtering problems. Ann. Appl. Probab., 8(2) :438–495 (1998).
40. P. Del Moral,, A. Doucet, & A. Jasra. Sequential Monte Carlo
samplers. J. R. Statist. Soc. B, 68, 411–436 (2006).
41. P. Del Moral,, A. Doucet, & A. Jasra. An Adaptive Sequential Monte Carlo
Method for Approximate Bayesian Computation Statistics and Computing, vol.
22, no. 5, pp. 1009–1020 (2012).
42. P. Del Moral, P. Hu, L. Wu. On the concentration properties of Interacting
particle processes. Foundations and Trends in Machine Learning, vol. 3, nos.
3–4, pp. 225–389 (2012).
43. P. Del Moral, A. Doucet, and A. Jasra. On adaptive resampling procedures for sequential Monte Carlo Bernoulli, vol. 18, no. 1, pp. 252-278 (2012).
44. P. Del Moral,, A. Doucet, & G. W. Peters. Sharp Propagations of
Chaos Estimates for Feynman-Kac particle Models Probability Theory and
its Applications SIAM, vol. 51, no. 3 (2006).
45. P. Del Moral, A. Doucet, and S. S. Singh. A Backward Particle Interpretation of Feynman-Kac Formulae. ESAIM M2AN, vol 44, no. 5, pp. 947–976
(2010).
46. P. Del Moral, A. Doucet, and S. S. Singh. Forward Smoothing Using Sequential Monte Carlo Technical Report 638. Cambridge University Engineering
Department (2010).
47. P. Del Moral, A. Doucet, and S. S. Singh. Uniform stability of a particle approximation of the optimal filter derivative. Technical Report CUED/FINFENG/TR 668. Cambridge University Engineering Department (2011).
48. P. Del Moral and J. Garnier. Genealogical particle analysis of rare
events. Ann. Appl. Probab., 15(4) :2496–2534 (2005).
49. P. Del Moral and J. Garnier. Simulations of rare events in fiber
optics by interacting particle systems. Optics Communications, Vol.
257, pp. 205-214 (2006).
50. P. Del Moral, J. Jacod. and P. Protter, The Monte-Carlo Method for
filtering with discrete-time observations, Probability Theory and Related Fields,
vol. 120, pp. 346–368, (2001).