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Interdisciplinary Research Centre
 

Department of Pure Mathematics and Mathematical Statistics Subscribe to RSS - Department of Pure Mathematics and Mathematical Statistics

Read more at: Paul Siewert

Paul Siewert

[pʰaʊ̯l ˈziː.vɛɐ̯tʰ]

I am a PhD student at Jesus College. My training is mathematical, but the main work I do with my supervisor Fermín Moscoso del Prado Martín is in mathematical linguistics. Please see my page on the Computer lab website for my non-linguistic interests.

"What counts is not what you cover, but what you uncover!"

Read more at: Professor John Aston

Professor John Aston

Statistical phonetics; spoken language evolution; functional data analysis for linguistics

Journal articles

2022 (Accepted for publication)

  • Jiang, C-R., Lila, E., Aston, J. and Wang, J-L., 2022 (Accepted for publication). Eigen-Adjusted Functional Principal Component Analysis Journal of Computational and Graphical Statistics,
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    2022

  • Lila, E. and Aston, JAD., 2022. Functional random effects modeling of brain shape and connectivity The Annals of Applied Statistics, v. 16
    Doi: 10.1214/21-aoas1572
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    2020

  • Lila, E., Arridge, S. and Aston, JAD., 2020. Representation and reconstruction of covariance operators in linear inverse problems Inverse Problems, v. 36
    Doi: 10.1088/1361-6420/ab8713
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    2019 (Accepted for publication)

  • Lila, E. and Aston, JAD., 2019 (Accepted for publication). Statistical Analysis of Functions on Surfaces, With an Application to Medical Imaging Journal of the American Statistical Association,
    Doi: http://doi.org/10.1080/01621459.2019.1635479
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    2019

  • Kashlak, AB., Aston, JAD. and Nickl, R., 2019. Inference on covariance operators via concentration inequalities: K-sample tests, classification, and clustering via rademacher complexities Sankhya: The Indian Journal of Statistics, v. 81A
    Doi: http://doi.org/10.1007/s13171-018-0143-9
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  • Ward, R., Choudhary, R., Heo, Y. and Aston, J., 2019. A data-centric bottom up model for generation of stochastic internal load profiles based on space-use type Journal of Building Performance Simulation,
    Doi: http://doi.org/10.1080/19401493.2019.1583287
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  • Olszowy, W., Aston, J., Rua, C. and Williams, GB., 2019. Accurate autocorrelation modeling substantially improves fMRI reliability. Nat Commun, v. 10
    Doi: http://doi.org/10.1038/s41467-019-09230-w
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  • Olszowy, W., Aston, J., Rua, C. and Williams, GB., 2019. Publisher Correction: Accurate autocorrelation modeling substantially improves fMRI reliability. Nat Commun, v. 10
    Doi: http://doi.org/10.1038/s41467-019-09619-7
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  • Debroux, N., Aston, J., Bonardi, F., Forbes, A., Le Guyader, C., Romanchikova, M. and Schonlieb, CB., 2019. A variational model dedicated to joint segmentation, registration, and atlas generation for shape analysis SIAM Journal on Imaging Sciences, v. 13
    Doi: http://doi.org/10.1137/19M1271907
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  • Tavakoli, S., Pigoli, D., Aston, JAD. and Coleman, JS., 2019. Rejoinder for “A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain” Journal of the American Statistical Association, v. 114
    Doi: http://doi.org/10.1080/01621459.2019.1655931
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  • Pascoal, TA., Mathotaarachchi, S., Kang, MS., Mohaddes, S., Shin, M., Park, AY., Parent, MJ., Benedet, AL., Chamoun, M., Therriault, J., Hwang, H., Cuello, AC., Misic, B., Soucy, J-P., Aston, JAD., Gauthier, S. and Rosa-Neto, P., 2019. Aβ-induced vulnerability propagates via the brain's default mode network. Nat Commun, v. 10
    Doi: http://doi.org/10.1038/s41467-019-10217-w
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  • Tavakoli, S., Pigoli, D., Aston, JAD. and Coleman, JS., 2019. A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain Journal of the American Statistical Association, v. 114
    Doi: http://doi.org/10.1080/01621459.2019.1607357
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    2018 (Accepted for publication)

  • Wang, Y., Dai, B., Hua, G., Aston, JAD. and Wipf, D., 2018 (Accepted for publication). Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers IEEE Journal on Selected Topics in Signal Processing,
    Doi: http://doi.org/10.1109/JSTSP.2018.2876995
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    2018

  • Dai, B., Wang, Y., Aston, J., Hua, G. and Wipf, D., 2018. Connections with robust PCA and the role of emergent sparsity in variational autoencoder models Journal of Machine Learning Research, v. 19
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    2017 (Accepted for publication)

  • Aston, J., Autin, F., Claeskens, G., Freyermuth, J-M. and Pouet, C., 2017 (Accepted for publication). Minimax optimal procedures for testing the structure of multidimensional functions Applied and Computational Harmonic Analysis,
    Doi: http://doi.org/10.1016/j.acha.2017.05.003
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  • Aston, JAD., Pigoli, D., Hadjipantelis, P. and Coleman, J., 2017 (Accepted for publication). The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages Journal of the Royal Statistical Society. Series C: Applied Statistics, v. 67
    Doi: http://doi.org/10.1111/rssc.12258
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    2017

  • Tirlea, MA., Tavakoli, S., Pigoli, D. and Aston, JAD., 2017. A ticklish problem: Studying accent variation from speech recordings Significance, v. 14
    Doi: http://doi.org/10.1111/j.1740-9713.2017.01019.x
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  • Lindsten, F., Johansen, AM., Naesseth, CA., Kirkpatrick, B., Schön, TB., Aston, JAD. and Bouchard-Côté, A., 2017. Divide-and-Conquer With Sequential Monte Carlo Journal of Computational and Graphical Statistics, v. 26
    Doi: http://doi.org/10.1080/10618600.2016.1237363
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  • Sayal, H., Aston, JAD., Elliott, D. and Ombao, H., 2017. An Introduction to Applications of Wavelet Benchmarking with Seasonal Adjustment Journal of the Royal Statistical Society Series A: Statistics in Society, v. 180
    Doi: 10.1111/rssa.12241
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  • Shiers, N., Aston, JAD., Smith, JQ. and Coleman, JS., 2017. Gaussian tree constraints applied to acoustic linguistic functional data Journal of Multivariate Analysis, v. 154
    Doi: http://doi.org/10.1016/j.jmva.2016.09.015
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  • Aston, JAD., Pigoli, D. and Tavakoli, S., 2017. Tests for separability in nonparametric covariance operators of random surfaces Annals of Statistics, v. 45
    Doi: http://doi.org/10.1214/16-AOS1495
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    2016

  • Shiers, N., Zwiernik, P., Aston, JAD. and Smith, JQ., 2016. The correlation space of Gaussian latent tree models and model selection without fitting Biometrika, v. 103
    Doi: http://doi.org/10.1093/biomet/asw032
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  • Jiang, C-R., Aston, JAD. and Wang, J-L., 2016. A Functional Approach to Deconvolve Dynamic Neuroimaging Data. J Am Stat Assoc, v. 111
    Doi: http://doi.org/10.1080/01621459.2015.1060241
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  • Lila, E., Aston, JAD. and Sangalli, LM., 2016. Smooth Principal Component Analysis over two-dimensional manifolds with an application to neuroimaging The Annals of Applied Statistics, v. 10
    Doi: 10.1214/16-aoas975
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  • Belavkin, RV., Channon, A., Aston, E., Aston, J., Krašovec, R. and Knight, CG., 2016. Monotonicity of fitness landscapes and mutation rate control. J Math Biol, v. 73
    Doi: http://doi.org/10.1007/s00285-016-0995-3
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  • Zhou, Y., Johansen, AM. and Aston, JAD., 2016. Toward Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach Journal of Computational and Graphical Statistics, v. 25
    Doi: http://doi.org/10.1080/10618600.2015.1060885
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    2015

  • Hadjipantelis, PZ., Aston, JAD., Müller, HG. and Evans, JP., 2015. Unifying Amplitude and Phase Analysis: A Compositional Data Approach to Functional Multivariate Mixed-Effects Modeling of Mandarin Chinese. J Am Stat Assoc, v. 110
    Doi: http://doi.org/10.1080/01621459.2015.1006729
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  • Nam, CFH., Aston, JAD., Eckley, IA. and Killick, R., 2015. The uncertainty of storm season changes: Quantifying the uncertainty of autocovariance changepoints Technometrics, v. 57
    Doi: http://doi.org/10.1080/00401706.2014.902776
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    2014

  • Hall, AJ., Chappell, MJ., Aston, JAD. and Ward, SA., 2014. Reprint of "Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin". Comput Methods Programs Biomed, v. 114
    Doi: http://doi.org/10.1016/j.cmpb.2013.12.001
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  • Krašovec, R., Belavkin, RV., Aston, JA., Channon, A., Aston, E., Rash, BM., Kadirvel, M., Forbes, S. and Knight, CG., 2014. Where antibiotic resistance mutations meet quorum-sensing. Microb Cell, v. 1
    Doi: http://doi.org/10.15698/mic2014.07.158
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  • Krašovec, R., Belavkin, RV., Aston, JAD., Channon, A., Aston, E., Rash, BM., Kadirvel, M., Forbes, S. and Knight, CG., 2014. Mutation rate plasticity in rifampicin resistance depends on Escherichia coli cell-cell interactions. Nat Commun, v. 5
    Doi: http://doi.org/10.1038/ncomms4742
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  • Aston, JAD., 2014. Comments on: Extensions of some classical methods in change point analysis DISCUSSION TEST, v. 23
    Doi: http://doi.org/10.1007/s11749-014-0369-3
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  • Nam, CFH., Aston, JAD. and Johansen, AM., 2014. Parallel sequential Monte Carlo samplers and estimation of the number of states in a Hidden Markov Model Annals of the Institute of Statistical Mathematics, v. 66
    Doi: http://doi.org/10.1007/s10463-014-0450-4
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  • Pigoli, D., Aston, JAD., Dryden, IL. and Secchi, P., 2014. Distances and inference for covariance operators Biometrika, v. 101
    Doi: http://doi.org/10.1093/biomet/asu008
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  • Aston, JAD. and Kirch, C., 2014. Efficiency of change point tests in high dimensional settings
  • Minas, G., Aston, JAD. and Stallard, N., 2014. Adaptive Multivariate Global Testing. J Am Stat Assoc, v. 109
    Doi: http://doi.org/10.1080/01621459.2013.870905
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  • Hadjipantelis, PZ., Aston, JAD., Müller, HG. and Moriarty, J., 2014. Analysis of spike train data: A multivariate mixed effects model for phase and amplitude Electronic Journal of Statistics,
    Doi: http://doi.org/10.1214/14-EJS865E
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    2013

  • Martin, DEK. and Aston, JAD., 2013. Distribution of Statistics of Hidden State Sequences Through the Sum-Product Algorithm Methodology and Computing in Applied Probability, v. 15
    Doi: http://doi.org/10.1007/s11009-012-9289-4
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  • Hall, AJ., Chappell, MJ., Aston, JAD. and Ward, SA., 2013. Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin. Comput Methods Programs Biomed, v. 112
    Doi: http://doi.org/10.1016/j.cmpb.2013.05.010
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  • Zhou, Y., Aston, JAD. and Johansen, AM., 2013. Bayesian model comparison for compartmental models with applications in positron emission tomography Journal of Applied Statistics, v. 40
    Doi: http://doi.org/10.1080/02664763.2013.772569
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  • Hindrayanto, I., Aston, JAD., Koopman, SJ. and Ooms, M., 2013. Modelling trigonometric seasonal components for monthly economic time series Applied Economics, v. 45
    Doi: http://doi.org/10.1080/00036846.2012.690937
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  • Sorrentino, A., Johansen, AM., Aston, JAD., Nichols, TE. and Kendall, WS., 2013. Dynamic filtering of static dipoles in magnetoencephalography Annals of Applied Statistics, v. 7
    Doi: http://doi.org/10.1214/12-AOAS611
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    2012

  • Nam, CFH., Aston, JAD. and Johansen, AM., 2012. Quantifying the uncertainty in change points Journal of Time Series Analysis, v. 33
    Doi: http://doi.org/10.1111/j.1467-9892.2011.00777.x
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  • Aston, JAD. and Kirch, C., 2012. Detecting and estimating changes in dependent functional data Journal of Multivariate Analysis, v. 109
    Doi: http://doi.org/10.1016/j.jmva.2012.03.006
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  • Aston, JAD., Peng, JY. and Martin, DEK., 2012. Implied distributions in multiple change point problems Statistics and Computing, v. 22
    Doi: http://doi.org/10.1007/s11222-011-9268-6
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  • Aston, JAD. and Kirch, C., 2012. Evaluating stationarity via change-point alternatives with applications to fMRI data Annals of Applied Statistics, v. 6
    Doi: http://doi.org/10.1214/12-AOAS565
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  • Vavoulis, DV., Straub, VA., Aston, JAD. and Feng, J., 2012. A self-organizing state-space-model approach for parameter estimation in hodgkin-huxley-type models of single neurons. PLoS Comput Biol, v. 8
    Doi: http://doi.org/10.1371/journal.pcbi.1002401
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  • Hadjipantelis, PZ., Aston, JAD. and Evans, JP., 2012. Characterizing fundamental frequency in Mandarin: a functional principal component approach utilizing mixed effect models. J Acoust Soc Am, v. 131
    Doi: http://doi.org/10.1121/1.4714345
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    2011

  • Chi, WC., Lee, WHK., Aston, JAD., Lin, CJ. and Liu, CC., 2011. Inversion of ground-motion data from a seismometer array for rotation using a modification of Jaeger's method Bulletin of the Seismological Society of America, v. 101
    Doi: http://doi.org/10.1785/0120100204
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  • Peng, JY. and Aston, JAD., 2011. The state space models toolbox for MATLAB Journal of Statistical Software, v. 41
    Doi: http://doi.org/10.18637/jss.v041.i06
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    2010

  • Evans, J., Chu, M-N., Aston, JAD. and Su, C-Y., 2010. Linguistic and human effects on F(0) in a tonal dialect of Qiang. Phonetica, v. 67
    Doi: http://doi.org/10.1159/000319380
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  • Cheng, PE., Liou, M. and Aston, JAD., 2010. Likelihood ratio tests with three-way tables Journal of the American Statistical Association, v. 105
    Doi: http://doi.org/10.1198/jasa.2010.tm09061
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  • Aston, JAD., Chiou, JM. and Evans, JP., 2010. Linguistic pitch analysis using functional principal component mixed effect models Journal of the Royal Statistical Society. Series C: Applied Statistics, v. 59
    Doi: http://doi.org/10.1111/j.1467-9876.2009.00689.x
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  • Wang, RH., Aston, JAD. and Fuh, CD., 2010. The Role of Additional Information in Option Pricing: Estimation Issues for the State Space Model Computational Economics, v. 36
    Doi: http://doi.org/10.1007/s10614-010-9240-0
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    2009

  • Lee, J-D., Su, H-R., Cheng, PE., Liou, M., Aston, JAD., Tsai, AC. and Chen, C-Y., 2009. MR image segmentation using a power transformation approach. IEEE Trans Med Imaging, v. 28
    Doi: http://doi.org/10.1109/TMI.2009.2012896
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  • Jiang, C-R., Aston, JAD. and Wang, J-L., 2009. Smoothing dynamic positron emission tomography time courses using functional principal components. Neuroimage, v. 47
    Doi: http://doi.org/10.1016/j.neuroimage.2009.03.051
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  • Liou, M., Su, H-R., Savostyanov, AN., Lee, J-D., Aston, JAD., Chuang, C-H. and Cheng, PE., 2009. Beyond p-values: averaged and reproducible evidence in fMRI experiments. Psychophysiology, v. 46
    Doi: http://doi.org/10.1111/j.1469-8986.2008.00780.x
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    2008

  • Martin, DEK. and Aston, JAD., 2008. Waiting time distribution of generalized later patterns Computational Statistics and Data Analysis, v. 52
    Doi: http://doi.org/10.1016/j.csda.2008.04.019
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  • Aston, JAD., Brown, EN., Loh, WL., Worsley, KJ. and Wu, Y., 2008. At the interface of statistics and brain science Statistica Sinica, v. 18
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  • Cheng, PE., Liou, M., Aston, JAD. and Tsai, AC., 2008. Information identities and testing hypotheses: Power analysis for contingency tables Statistica Sinica, v. 18
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  • Peng, J-Y., Aston, JAD., Gunn, RN., Liou, C-Y. and Ashburner, J., 2008. Dynamic positron emission tomography data-driven analysis using sparse Bayesian learning. IEEE Trans Med Imaging, v. 27
    Doi: http://doi.org/10.1109/TMI.2008.922185
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  • Aston, JAD., Fuh, CD. and Luo, SF., 2008. Discussion on "Is average run length to false alarm always an informative criterion?" by Yajun Mei Sequential Analysis, v. 27
    Doi: http://doi.org/10.1080/07474940802445899
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    2007

  • Peng, J-Y. and Aston, JAD., 2007. The SSM Toolbox for Matlab
  • Aston, JAD., 2007. Modeling macroeconomic time series via heavy tailed distributions IMS Lecture Notes Monograph Series, v. 52
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  • Aston, JAD. and Martin, DEK., 2007. Distributions associated with general runs and patterns in hidden Markov models Annals of Applied Statistics, v. 1
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    2006

  • Turkheimer, FE., Aston, JAD., Asselin, M-C. and Hinz, R., 2006. Multi-resolution Bayesian regression in PET dynamic studies using wavelets. Neuroimage, v. 32
    Doi: http://doi.org/10.1016/j.neuroimage.2006.03.002
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  • Liou, M., Su, H-R., Lee, J-D., Aston, JAD., Tsai, AC. and Cheng, PE., 2006. A method for generating reproducible evidence in fMRI studies. Neuroimage, v. 29
    Doi: http://doi.org/10.1016/j.neuroimage.2005.08.015
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    2005

  • Aston, JAD. and Martin, DEK., 2005. Waiting time distributions of competing patterns in higher-order Markovian sequences Journal of Applied Probability, v. 42
    Doi: http://doi.org/10.1239/jap/1134587810
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  • Aston, JAD., Gunn, RN., Hinz, R. and Turkheimer, FE., 2005. Wavelet variance components in image space for spatiotemporal neuroimaging data. Neuroimage, v. 25
    Doi: http://doi.org/10.1016/j.neuroimage.2004.10.037
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    2004

  • Turkheimer, FE., Aston, JAD. and Cunningham, VJ., 2004. On the logic of hypothesis testing in functional imaging. Eur J Nucl Med Mol Imaging, v. 31
    Doi: http://doi.org/10.1007/s00259-003-1387-7
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    2003

  • Turkheimer, FE., Hinz, R., Gunn, RN., Aston, JAD., Gunn, SR. and Cunningham, VJ., 2003. Rank-shaping regularization of exponential spectral analysis for application to functional parametric mapping. Phys Med Biol, v. 48
    Doi: http://doi.org/10.1088/0031-9155/48/23/002
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    2000

  • Turkheimer, FE., Brett, M., Aston, JA., Leff, AP., Sargent, PA., Wise, RJ., Grasby, PM. and Cunningham, VJ., 2000. Statistical modeling of positron emission tomography images in wavelet space. J Cereb Blood Flow Metab, v. 20
    Doi: http://doi.org/10.1097/00004647-200011000-00011
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    Theses / dissertations

    2021 (No publication date)

  • Goucher, AP., 2021 (No publication date). Topological and geometric inference of data
    • Datasets

    2017 (No publication date)

  • Aston, J., Pigoli, D., Hadjipantelis, P. and Coleman, J., 2017 (No publication date). Research data supporting "The statistical analysis of acoustic phonetic data:exploring differences between spoken Romance languages"
    Doi: http://doi.org/10.17863/CAM.17139
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    Conference proceedings

    2017

  • Wang, Y., Dai, B., Hua, G., Aston, J. and Wipf, D., 2017. Green generative modeling: Recycling dirty data using recurrent variational autoencoders Uncertainty in Artificial Intelligence - Proceedings of the 33rd Conference, UAI 2017,
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  • Pascoal, TA., Mathotaarachchi, S., Kang, MS., Shin, M., Park, AY., Parent, M., Ng, KP., Soucy, J-P., Aston, JAD., Cuello, C., Gauthier, S. and Rosa-Neto, P., 2017. Global and regional amyloid-β effects on default model network drive progression to AD dementia JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, v. 37
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    2012

  • Hall, AJ., Chappell, MJ., Aston, JAD. and Ward, SA., 2012. Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin IFAC Proceedings Volumes (IFAC-PapersOnline), v. 45
    Doi: http://doi.org/10.3182/20120829-3-HU-2029.00039
    •
  • Zhou, Y., Johansen, AM. and Aston, JAD., 2012. Bayesian model comparison via path-sampling sequential Monte Carlo 2012 IEEE Statistical Signal Processing Workshop, SSP 2012,
    Doi: http://doi.org/10.1109/SSP.2012.6319672
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    2011

  • Peng, JY., Aston, JAD. and Liou, CY., 2011. Modeling time series and sequences using Markov chain embedded finite automata International Journal of Innovative Computing, Information and Control, v. 7
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    2009

  • Martin, DEK. and Aston, JAD., 2009. Exact distribution of statistics of hidden state sequences via message passing in factor graphs AIP Conference Proceedings, v. 1127
    Doi: http://doi.org/10.1063/1.3146186
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    2008

  • Su, HR., Liou, M., Cheng, PE., Aston, JAD. and Lai, SH., 2008. Reproducibility analysis of event-related fMRI experiments using Laguerre polynomials Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 4984 LNCS
    Doi: http://doi.org/10.1007/978-3-540-69158-7_14
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    2006

  • Aston, JAD., Turkheimer, FE. and Brett, M., 2006. HBM functional imaging analysis contest data analysis in wavelet space. Hum Brain Mapp, v. 27
    Doi: http://doi.org/10.1002/hbm.20244
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    What we do

    Cambridge Language Sciences is an Interdisciplinary Research Centre at the University of Cambridge. Our virtual network connects researchers from five schools across the university as well as other world-leading research institutions. Our aim is to strengthen research collaborations and knowledge transfer across disciplines in order to address large-scale multi-disciplinary research challenges relating to language research.

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