User profiles for A. Doucet

Arnaud Doucet

- Verified email at stats.ox.ac.uk - Cited by 62751

Andrea Doucet

- Verified email at brocku.ca - Cited by 9421

Sodium-potassium-adenosinetriphosphatase-dependent sodium transport in the kidney: hormonal control

E Feraille, A Doucet - Physiological reviews, 2001 - journals.physiology.org
Tubular reabsorption of filtered sodium is quantitatively the main contribution of kidneys to
salt and water homeostasis. The transcellular reabsorption of sodium proceeds by a two-step …

[PDF][PDF] A tutorial on particle filtering and smoothing: Fifteen years later

A Doucet, AM Johansen - Handbook of nonlinear filtering, 2009 - warwick.ac.uk
Optimal estimation problems for non-linear non-Gaussian state-space models do not typically
admit analytic solutions. Since their introduction in 1993, particle filtering methods have …

On particle methods for parameter estimation in state-space models

N Kantas, A Doucet, SS Singh, J Maciejowski… - 2015 - projecteuclid.org
Nonlinear non-Gaussian state-space models are ubiquitous in statistics, econometrics,
information engineering and signal processing. Particle methods, also known as Sequential …

[BOOK][B] Sequential Monte Carlo methods in practice

A Doucet, N De Freitas, NJ Gordon - 2001 - Springer
Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as
financial modelling, target tracking and computer vision. These methods, appearing under …

On sequential Monte Carlo sampling methods for Bayesian filtering

A Doucet, S Godsill, C Andrieu - Statistics and computing, 2000 - Springer
In this article, we present an overview of methods for sequential simulation from posterior
distributions. These methods are of particular interest in Bayesian filtering for discrete time …

[HTML][HTML] An introduction to MCMC for machine learning

C Andrieu, N De Freitas, A Doucet, MI Jordan - Machine learning, 2003 - Springer
This purpose of this introductory paper is threefold. First, it introduces the Monte Carlo method
with emphasis on probabilistic machine learning. Second, it reviews the main building …

Sequential monte carlo samplers

P Del Moral, A Doucet, A Jasra - Journal of the Royal Statistical …, 2006 - academic.oup.com
We propose a methodology to sample sequentially from a sequence of probability distributions
that are defined on a common space, each distribution being known up to a normalizing …

An introduction to sequential Monte Carlo methods

A Doucet, N De Freitas, N Gordon - Sequential Monte Carlo methods in …, 2001 - Springer
Many real-world data analysis tasks involve estimating unknown quantities from some given
observations. In most of these applications, prior knowledge about the phenomenon being …

The unscented particle filter

R Van Der Merwe, A Doucet… - Advances in neural …, 2000 - proceedings.neurips.cc
In this paper, we propose a new particle filter based on sequential importance sampling.
The algorithm uses a bank of unscented fil (cid: 173) ters to obtain the importance proposal …

Particle markov chain monte carlo methods

C Andrieu, A Doucet… - Journal of the Royal …, 2010 - academic.oup.com
Markov chain Monte Carlo and sequential Monte Carlo methods have emerged as the two
main tools to sample from high dimensional probability distributions. Although asymptotic …