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09/15/2023
On the Forgetting of Particle Filters
We study the forgetting properties of the particle filter when its state...
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11/22/2022
Quasi-Newton Sequential Monte Carlo
Sequential Monte Carlo samplers represent a compelling approach to poste...
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06/21/2022
De-biasing particle filtering for a continuous time hidden Markov model with a Cox process observation model
We develop a (nearly) unbiased particle filtering algorithm for a specif...
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05/27/2022
Conditional particle filters with bridge backward sampling
The performance of the conditional particle filter (CPF) with backward s...
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03/24/2022
Multilevel Bayesian Deep Neural Networks
In this article we consider Bayesian inference associated to deep neural...
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03/18/2022
On resampling schemes for particle filters with weakly informative observations
We consider particle filters with weakly informative observations (or `p...
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10/06/2021
Ensemble Kalman Inversion for General Likelihoods
Ensemble Kalman inversion represents a powerful technique for inference ...
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12/20/2020
Dimension-robust Function Space MCMC With Neural Network Priors
This paper introduces a new prior on functions spaces which scales more ...
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12/08/2020
Online Particle Smoothing with Application to Map-matching
We introduce a novel method for online smoothing in state-space models b...
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06/26/2020
Anytime Parallel Tempering
Developing efficient and scalable Markov chain Monte Carlo (MCMC) algori...
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06/18/2018
Stability of Conditional Sequential Monte Carlo
The particle Gibbs (PG) sampler is a Markov Chain Monte Carlo (MCMC) alg...
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06/15/2018
Coupled conditional backward sampling particle filter
We consider the coupled conditional backward sampling particle filter (C...
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04/19/2018
On Large Lag Smoothing for Hidden Markov Models
In this article we consider the smoothing problem for hidden Markov mode...
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03/26/2018
On the loss of Fisher information in some multi-object tracking observation models
The concept of Fisher information can be useful even in cases where the ...
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11/08/2017
Multilevel Monte Carlo for Smoothing via Transport Methods
In this article we consider recursive approximations of the smoothing di...
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03/17/2016
Tracking multiple moving objects in images using Markov Chain Monte Carlo
A new Bayesian state and parameter learning algorithm for multiple targe...
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10/08/2014
Bayesian tracking and parameter learning for non-linear multiple target tracking models
We propose a new Bayesian tracking and parameter learning algorithm for ...
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01/11/2014
An Online Expectation-Maximisation Algorithm for Nonnegative Matrix Factorisation Models
In this paper we formulate the nonnegative matrix factorisation (NMF) pr...
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11/26/2012