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Statistical Laboratory

Publications

Accurate autocorrelation modelling substantially improves fMRI reliability
W Olszowy, J Aston, C Rua, GB Williams
– Nature communications
(2019)
10,
1220
Rejoinder for “A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain”
S Tavakoli, D Pigoli, JAD Aston, JS Coleman
– Journal of the American Statistical Association
(2019)
114,
1103
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
– Journal of the American Statistical Association
(2019)
114,
1081
Aβ-induced vulnerability propagates via the brain's default mode network.
TA Pascoal, S Mathotaarachchi, MS Kang, S Mohaddes, M Shin, AY Park, MJ Parent, AL Benedet, M Chamoun, J Therriault, H Hwang, AC Cuello, B Misic, J-P Soucy, JAD Aston, S Gauthier, P Rosa-Neto
– Nature Communications
(2019)
10,
2353
Publisher Correction: Accurate autocorrelation modeling substantially improves fMRI reliability (Nature Communications, (2019), 10, 1, (1220), 10.1038/s41467-019-09230-w)
W Olszowy, J Aston, C Rua, GB Williams
– Nat Commun
(2019)
10,
1511
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,
620
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 of 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
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