61 citations · 294 across the 31 of their papers we have counts for
4 papers · 1 filter
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…
Twisted particle filters
Nick Whiteley, Anthony Lee
We investigate sampling laws for particle algorithms and the influence of these laws on the efficiency of particle approximations of marginal likelihoods in hidden Markov models. A…
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…
Calculating principal eigen-functions of non-negative integral kernels: particle approximations and applications
Nick Whiteley, Nikolas Kantas
Often in applications such as rare events estimation or optimal control it is required that one calculates the principal eigen-function and eigen-value of a non-negative integral k…