7 citations · 8 across the 3 of their papers we have counts for
11 papers
Robust Bayesian inference in complex models with possibility theory
Jeremie Houssineau, David J. Nott
We propose a general solution to the problem of robust Bayesian inference in complex settings where outliers may be present. In practice, the automation of robust Bayesian analyses…
On Unbiased Score Estimation for Partially Observed Diffusions
Jeremy Heng, Jeremie Houssineau, Ajay Jasra
We consider the problem of statistical inference for a class of partially-observed diffusion processes, with discretely-observed data and finite-dimensional parameters. We construc…
Uncertainty modelling and computational aspects of data association
Jeremie Houssineau, Jiajie Zeng, Ajay Jasra
A novel solution to the smoothing problem for multi-object dynamical systems is proposed and evaluated. The systems of interest contain an unknown and varying number of dynamical o…
Target tracking in the framework of possibility theory: The possibilistic Bernoulli filter
Branko Ristic, Jeremie Houssineau, Sanjeev Arulampalam
The Bernoulli filter is a Bayes filter for joint detection and tracking of a target in the presence of false and miss detections. This paper presents a mathematical formulation of…
Elements of asymptotic theory with outer probability measures
Jeremie Houssineau, Neil K. Chada, Emmanuel Delande
Outer measures can be used for statistical inference in place of probability measures to bring flexibility in terms of model specification. The corresponding statistical procedures…
Robust TMA using the possibility particle filter
Branko Ristic, Jeremie Houssineau, Sanjeev Arulampalam
The problem is target motion analysis (TMA), where the objective is to estimate the state of a moving target from noise corrupted bearings-only measurements. The focus is on recurs…