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04/16/2022
Nested smoothing algorithms for inference and tracking of heterogeneous multi-scale state-space systems
Multi-scale problems, where variables of interest evolve in different ti...
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04/15/2022
Space-sequential particle filters for high-dimensional dynamical systems described by stochastic differential equations
We introduce a novel methodology for particle filtering in dynamical sys...
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06/11/2021
Polynomial propagation of moments in stochastic differential equations
We address the problem of approximating the moments of the solution, X(t...
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03/23/2021
Nested Gaussian filters for recursive Bayesian inference and nonlinear tracking in state space models
We introduce a new sequential methodology to calibrate the fixed paramet...
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11/04/2019
New results on particle filters with adaptive number of particles
In this paper, we present new results on particle filters with adaptive ...
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03/28/2019
Convergence rates for optimised adaptive importance samplers
Adaptive importance samplers are adaptive Monte Carlo algorithms to esti...
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12/04/2018
A probabilistic incremental proximal gradient method
In this paper, we propose a probabilistic optimization method, named pro...
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11/23/2018
Parallel sequential Monte Carlo for stochastic optimization
We propose a parallel sequential Monte Carlo optimization method to mini...
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09/02/2018
Stable approximation schemes for optimal filters
We explore a general truncation scheme for the approximation of (possibl...
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07/12/2018
The Incremental Proximal Method: A Probabilistic Perspective
In this work, we highlight a connection between the incremental proximal...
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08/25/2017
Nudging the Particle Filter
We investigate a new sampling scheme to improve the performance of parti...
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08/11/2017