Whiteley, Gray and Rubin-Delanchy. Statistical exploration of the Manifold Hypothesis. 2023.

Gray, Modell, Rubin-Delanchy and Whiteley. Hierarchical clustering with dot products recovers hidden tree structure. NeurIPS Spotlight. 2023

Modell, Gallagher, Ceccherini, Whiteley, Rubin-Delanchy. Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks. NeurIPS 2023

Sansford, Modell, Whiteley and Rubin-Delanchy. Implications of sparsity and high triangle density for graph representation learning. AISTATS notable paper. 2023.

Whitehouse, Whiteley and Rimella. Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods. JRSSB. To appear.

Whiteley, Jones and Domanski. The infinite Viterbi alignment and decay-convexity. Bernoulli. To appear.

Dai, Heng, Jacob and Whiteley. An invitation to Sequential Monte Carlo Samplers. Journal of the American Statistical Association. 2022.

Rimella and Whiteley. Exploiting locality in high-dimensional factorial hidden Markov models. Journal of Machine Learning Research. 2022.

Whiteley. Dimension-free Wasserstein contraction of nonlinear filters. Stochastic Processes and their Applications. 2021.

Rendell, Johansen, Lee and Whiteley. Global consensus Monte Carlo. Journal of Computational and Graphical Statistics. 2020.

Heine, Whiteley and Cemgil. Parallelising Particle Filters with Butterfly Interactions. Scandinavian Journal of Statistics. 2019.

Gerber, Chopin and Whiteley. Negative association, ordering and convergence of resampling methods. The Annals of Statistics. 2019.

Lee and Whiteley. Variance estimation in the particle filter. Biometrika. 2018.

O’Donnell, Goncalves, Whiteley, Portera-Cailliau and Sejnowski. The population tracking model: A simple, scalable statistical model for neural population data. Neural Computation. 2017.

Heine and Whiteley. Fluctuations, stability and instability of a distributed particle filter with local exchange.  Stochastic Processes and their Applications. 2017.

Kostov and Whiteley. An algorithm for approximating the second moment of the normalizing constant estimate from a particle filter. Methodology and Computing in Applied Probability. 2017.

Gerber and Whiteley. Stability with respect to initial conditions in V-norm for nonlinear filters with ergodic observations. Journal of Applied Probability. 2017.

Whiteley and Kantas. Calculating principal eigen-functions of non-negative integral kernels: particle approximations and applications. Mathematics of Operations Research. 2017.

Box, Jones and Whiteley. A hidden Markov model for decoding and the analysis of replay in spike trains. Journal of Computational Neuroscience. 2016.

Ala-Luhtala,  Whiteley, Heine and Piché. An Introduction to Twisted Particle Filters and Parameter Estimation in Non-Linear State-Space Models. IEEE Transactions on Signal Processing. 2016.

Whiteley and Lee. Perfect Sampling for nonhomogeneous Markov chains and hidden Markov models. The Annals of Applied Probability. 2016.

Whiteley, Lee and Heine. On the role of interaction in sequential Monte Carlo algorithms, Bernoulli. 2016.

Lee and Whiteley. Forest resampling for distributed sequential Monte Carlo, Statistical Analysis and Data Mining. 2015.

Whiteley and Lee. Twisted Particle Filters. The Annals of Statistics. 2014.

Martin, Jasra, Singh, Whiteley, Del Moral and McCoy. Approximate Bayesian Computation for Smoothing. Stochastic Analysis and Applications. 2014.

Beskos, Crisan, Jasra and Whiteley. Error bounds and normalizing constants for sequential Monte Carlo samplers in high dimensions. Advances in Applied Probability. 2014.

Singh, Chopin  and Whiteley. Bayesian Learning of Noisy Markov Decision Processes. ACM Transactions on Modeling and Computer Simulation. 2013. 

Whiteley. Stability properties of some particle filters. Annals of Applied Probability. 2013.

Whiteley. Sequential Monte Carlo Samplers: error bounds and insensitivity to initial conditions. Stochastic Analysis and Applications. 2012.

Whiteley, Kantas and Jasra. Linear variance bounds for particle approximations of time-homogeneous Feynman-Kac formulae. Stochastic Processes and their Applications. 2012.

Whiteley, Johansen and Godsill. Monte Carlo filtering of piece-wise deterministic processes. Journal of Computational and Graphical Statistics. 2011.

Whiteley, Singh  and Godsill. Auxiliary particle implementation of the Probability Hypothesis Density Filter. IEEE Transactions on Aerospace and Electronic Systems. 2010.

Gray, Modell, Rubin-Delanchy and Whiteley. Hierarchical clustering with dot products recovers hidden tree structure. NeurIPS Spotlight. 2023.

Modell, Gallagher, Ceccherini, Whiteley, Rubin-Delanchy. Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks. NeurIPS 2023.

Sansford, Modell, Whiteley and Rubin-Delanchy. Implications of sparsity and high triangle density for graph representation learning. AISTATS. 2023.

Whiteley, Gray and Rubin-Delanchy. Matrix factorisation and the interpretation of geodesic distance. NeurIPS 2021.

Whiteley and Rimella. Inference in stochastic epidemic models via multinomial approximations. AISTATS 2021.

Guldas, Cemgil, Whiteley and Heine. A practical introduction to butterfly and adaptive resampling in Sequential Monte Carlo. Invited paper. In Proceedings of 17th IFAC Symposium on Systems Identification. 2015.

Pereyra, Whiteley, Andrieu and Tourneret. Maximum marginal likelihood estimation of the granularity coefficient of a Potts-Markov random field within an MCMC algorithm. IEEE SSP Workshop. 2014.

Johansen, Whiteley and Doucet. Exact approximation of Rao-Blackwellised particle filters.  In Proceedings of 16th IFAC Symposium on System Identification. 2014.

Whiteley, Cemgil and Godsill. Sequential Inference of Rhythmic Structure in Musical Audio. IEEE ICASSP. 2007.

Whiteley, Cemgil and Godsill. Bayesian Modelling of Temporal Structure in Musical Audio. ISMIR. 2006.

Whiteley and Johanse. Recent Developments in Auxiliary Particle Filtering , Whiteley and Johansen, Bayesian Time Series Models. 2011.

Singh, Whiteley and Godsill. Approximate likelihood estimation of static parameters in multi-target models. Bayesian Time Series Models.  2011.

Cemgil, Godsill, Peeling and Whiteley. Bayesian statistical methods for audio and music processing. A. Taylan Cemgil, Simon J. Godsill, Paul Peeling, Nick Whiteley.  The Oxford Handbook of Applied Bayesian Analysis. 2010.

Discussion of "Particle Markov chain Monte Carlo methods" by Andrieu, Doucet and Holenstein, Journal of the Royal Statistical Society: Series B. 2010.

Whiteley. Dynamic clustering of time series via volatility change-points. 

Andrieu, Ridgway and Whiteley. Sampling normalizing constants in high dimensions using inhomogeneous diffusions.

Whiteley, Andrieu and Doucet. Efficient Bayesian Inference for Switching State-Space Models using Discrete Particle Markov Chain Monte Carlo Methods.

Whiteley, Andrieu, Doucet. Bayesian Computational Methods for Inference in Multiple Change-points Models.