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Bayesian State-Space Modelling on High-Performance Hardware Using LibBi

Bayesian State-Space Modelling on High-Performance Hardware Using LibBi

L.M. Murray

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Parallel Resampling in the Particle Filter

Parallel Resampling in the Particle Filter

L.M. Murray, A. Lee and P.E. Jacob

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Path Storage in the Particle Filter

Path Storage in the Particle Filter

P.E. Jacob, L.M. Murray and S. Rubenthaler

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Rethinking soil carbon modelling: a stochastic approach to quantify uncertainties

D. Clifford, D. Pagendam, J. Baldock, N. Cressie, R. Farquharson, M. Farrell, L. Macdonald and L.M. Murray

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Bayesian Learning and Predictability in a Stochastic Nonlinear Dynamical Model

J. Parslow, N. Cressie and E.P. Campbell, E. Jones and L.M. Murray

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On Disturbance State-Space Models and the Particle Marginal Metropolis--Hastings Sampler

On Disturbance State-Space Models and the Particle Marginal Metropolis--Hastings Sampler

L.M. Murray, E.M. Jones and J. Parslow

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Feynman-Kac Particle Integration with Geometric Interacting Jumps

P. Del Moral, P.E. Jacob, A. Lee, L.M. Murray and G.W. Peters

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GPU Acceleration of Runge-Kutta Integrators

L.M. Murray

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Assimilation of glider and mooring data into a coastal ocean model

E.M. Jones, P.R. Oke, F. Rizwi and L.M. Murray

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Particle smoothing in continuous time: A fast approach via density estimation

L.M. Murray and A. Storkey

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High-Performance Pseudo-Random Number Generation on Graphics Processing Units

N. Nandapalan, R. Brent, L.M. Murray and A. Rendell

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GPU acceleration of the particle filter: The Metropolis resampler

L.M. Murray