Approximation of transition densities of stochastic differential equations by saddlepoint methods applied to small-time Ito-Taylor sample-path expansions. - S. P. Preston; Andrew T. A. Wood (Stat. Comput., 2012)

AMP: a new time-frequency feature extraction method for intermittent time-series data. - Duncan Barrack; James Goulding; Keith Hopcraft; Simon Preston; Gavin Smith (CoRR, 2015)

Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution. - Simon R. White; Theodore Kypraios; S. P. Preston (Stat. Comput., 2015)

Event Series Prediction via Non-Homogeneous Poisson Process Modelling. - James Goulding; Simon Preston; Gavin Smith (ICDM, 2016)

Improved Classification for Compositional Data Using the α-transformation. - Michail Tsagris; Simon Preston; Andrew T. A. Wood (J. Classif., 2016)

Classification and clustering for samples of event time data using non-homogeneous Poisson process models. - Duncan Barrack; James Goulding; Simon Preston (CoRR, 2017)

An elliptically symmetric angular Gaussian distribution. - P. J. Paine; S. P. Preston; Michail Tsagris; Andrew T. A. Wood (Stat. Comput., 2018)

Invariance and identifiability issues for word embeddings. - Rachel Carrington; Karthik Bharath; Simon Preston (NeurIPS, 2019)

Spherical regression models with general covariates and anisotropic errors. - P. J. Paine; S. P. Preston; Michail Tsagris; Andrew T. A. Wood (Stat. Comput., 2020)

Non-parametric regression for robot learning on manifolds. - Pablo C. López-Custodio; Karthik Bharath; A. Kucukyilmaz; S. P. Preston (CoRR, 2023)