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On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
Sarah Filippi, Chris Barnes, Julien Cornebise +1
Approximate Bayesian computation (ABC) has gained popularity over the past few years for the analysis of complex models arising in population genetic, epidemiology and system biolo…
Discussion of "Riemann manifold Langevin and Hamiltonian Monte Carlo methods'' by M. Girolami and B. Calderhead
Luke Bornn, Julien Cornebise, Gareth W. Peters
This technical report is the union of two contributions to the discussion of the Read Paper "Riemann manifold Langevin and Hamiltonian Monte Carlo methods" by B. Calderhead and M.…
Adaptive methods for sequential importance sampling with application to state space models
Julien Cornebise, Eric Moulines, Jimmy Olsson
In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on criteria evaluating the quality of the p…