362 citations · 635 across the 29 of their papers we have counts for
5 papers · 1 filter
Estimating the Static Parameters in Linear Gaussian Multiple Target Tracking Models
Sinan Yildirim, Lan Jiang, Sumeetpal S. Singh +1
We present both offline and online maximum likelihood estimation (MLE) techniques for inferring the static parameters of a multiple target tracking (MTT) model with linear Gaussian…
Bayesian learning of noisy Markov decision processes
Sumeetpal S. Singh, Nicolas Chopin, Nick Whiteley
We consider the inverse reinforcement learning problem, that is, the problem of learning from, and then predicting or mimicking a controller based on state/action data. We propose…
Approximate Bayesian Computation for Smoothing
James S. Martin, Ajay Jasra, Sumeetpal S. Singh +2
We consider a method for approximate inference in hidden Markov models (HMMs). The method circumvents the need to evaluate conditional densities of observations given the hidden st…
Distributed Maximum Likelihood for Simultaneous Self-localization and Tracking in Sensor Networks
Nikolas Kantas, Sumeetpal S. Singh, Arnaud Doucet
We show that the sensor self-localization problem can be cast as a static parameter estimation problem for Hidden Markov Models and we implement fully decentralized versions of the…
Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation"
Christophe Andrieu, Simon Barthelme, Nicolas Chopin +11
This report is a collection of comments on the Read Paper of Fearnhead and Prangle (2011), to appear in the Journal of the Royal Statistical Society Series B, along with a reply fr…