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The Statistics Clinic

Professor of Statistics

Research Interests: Statistics: in particular Functional / Object Data Analysis, Time Series Analysis, Statistical Neuroimaging, Statistical Linguistics, Seasonal Adjustment and other Applied Statistics

Publications

A variational model dedicated to joint segmentation, registration, and atlas generation for shape analysis
N Debroux, J Aston, F Bonardi, A Forbes, C Le Guyader, M Romanchikova, CB Schonlieb
– SIAM Journal on Imaging Sciences
(2020)
13,
351
Statistical Analysis of Functions on Surfaces, With an Application to Medical Imaging
E Lila, JAD Aston
– Journal of the American Statistical Association
(2019)
115,
1
A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain
S Tavakoli, D Pigoli, JAD Aston, JS Coleman
– ournal of the American Statistical Association (Theory & Methods)
(2019)
114,
1081
Publisher Correction: Accurate autocorrelation modeling substantially improves fMRI reliability
W Olszowy, J Aston, C Rua, GB Williams
– Nat Commun
(2019)
10,
1511
Accurate autocorrelation modeling substantially improves fMRI reliability.
W Olszowy, J Aston, C Rua, GB Williams
– Nat Commun
(2019)
10,
1220
A data-centric bottom up model for generation of stochastic internal load profiles based on space-use type
R Ward, R Choudhary, Y Heo, J Aston
– Journal of Building Performance Simulation
(2019)
12,
1
Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers
Y Wang, B Dai, G Hua, JAD Aston, D Wipf
– IEEE Journal on Selected Topics in Signal Processing
(2018)
12,
1615
The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages
JAD Aston, D Pigoli, P Hadjipantelis, J Coleman
– Journal of the Royal Statistical Society. Series C: Applied Statistics
(2018)
67,
1103
Connections with robust PCA and the role of emergent sparsity in variational autoencoder models
B Dai, Y Wang, J Aston, G Hua, D Wipf
– Journal of Machine Learning Research
(2018)
19,
1
Inference on Covariance Operators via Concentration Inequalities: k-sample Tests, Classification, and Clustering via Rademacher Complexities
AB Kashlak, JAD Aston, R Nickl
– Sankhya A
(2018)
81,
214
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Research Group

Statistics Clinic

Room

D1.03

Telephone

01223 766535