PhD supervision
PhD supervision
Hannah Sansford
Sansford, Whiteley and Rubin-Delanchy. How high is 'high'? Rethinking the roles of dimensionality in topolgical data analysis and manifold learning. 2025.
Sansford, Modell, Whiteley and Rubin-Delanchy. Implications of sparsity and high triangle density for graph representation learning. AISTATS 2023.
Dominic Broadbent
Broadbent, Whiteley, Allison and Lovett. Conditional Distribution Compression via the Kernel Conditional Mean Embedding. 2025.
Michael Whitehouse
Whitehouse, Whiteley and Rimella. Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods. JRSSB 2023.
Annie Gray
Gray, Modell, Whiteley, and Rubin-Delanchy. Hierarchical clustering with dot products recovers hidden tree structure. NeurIPS 2023 spotlight.
Whiteley, Gray and Rubin-Delanchy. Matrix factorisation and the interpretation of geodesic distance. NeurIPS 2021.
Whiteley, Gray and Rubin-Delanchy. Statistical exploration of the Manifold Hypothesis. 2024
Lorenzo Rimella
Rimella and Whiteley. Exploiting locality in high-dimensional factorial hidden Markov models. JMLR
Whiteley and Rimella. Inference in stochastic epidemic models via multinomial approximations. AISTATS 2021.
Juha Ala-Luhtala
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.
Svetoslav Kostov
Kostov. Hamiltonian Sequential Monte Carlo and Normalizing Constants. Ph.D. Thesis. 2016.
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.
Marc Box
Box, Jones and Whiteley. A hidden Markov model for decoding and the analysis of replay in spike trains. Journal of Computational Neuroscience. 2016.