John A. D. Aston

According to our database, John A. D. Aston authored at least 36 papers between 2002 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Navigating the development challenges in creating complex data systems.

Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb

Nat. Mac. Intell., July, 2023

Recent Methodological Advances in Federated Learning for Healthcare.

Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, BloodCounts Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts

CoRR, 2023

Reinterpreting survival analysis in the universal approximator age.

Sören Dittmer, Michael Roberts, Jacobus Preller, AIX-COVNET Collaboration, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb

CoRR, 2023

Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data.

Daniel Kreuter, Samuel Tull, Julian D. Gilbey, Jacobus Preller, BloodCounts Consortium, John A. D. Aston, James H. F. Rudd, Suthesh Sivapalaratnam, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts

CoRR, 2023

2022

Eigen-Adjusted Functional Principal Component Analysis.

Ci-Ren Jiang, Eardi Lila, John A. D. Aston, Jane-Ling Wang

J. Comput. Graph. Stat., October, 2022

On Krylov Methods for Large Scale CBCT Reconstruction.

Malena Sabate Landman, Ander Biguri, Sepideh Hatamikia, Richard P. Boardman, John A. D. Aston, Carola-Bibiane Schönlieb

CoRR, 2022

Navigating the challenges in creating complex data systems: a development philosophy.

Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, AIX-COVNET Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb

CoRR, 2022

Classification of datasets with imputed missing values: does imputation quality matter?

Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb

CoRR, 2022

Testing for Geometric Invariance and Equivariance.

Louis G. Christie, John A. D. Aston

CoRR, 2022

2020

A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis.

Noémie Debroux, John A. D. Aston, Fabien Bonardi, Alistair Forbes, Carole Le Guyader, Marina Romanchikova, Carola-Bibiane Schönlieb

SIAM J. Imaging Sci., 2020

2018

Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers.

Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf

IEEE J. Sel. Top. Signal Process., 2018

Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models.

Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf

J. Mach. Learn. Res., 2018

2017

Gaussian tree constraints applied to acoustic linguistic functional data.

Nathaniel Shiers, John A. D. Aston, Jim Q. Smith, John S. Coleman

J. Multivar. Anal., 2017

Veiled Attributes of the Variational Autoencoder.

Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf

CoRR, 2017

Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders.

Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2015

The Uncertainty of Storm Season Changes: Quantifying the Uncertainty of Autocovariance Changepoints.

Christopher F. H. Nam, John A. D. Aston, Idris A. Eckley, Rebecca Killick

Technometrics, 2015

Reconstructing the sounds of words from the past.

John S. Coleman, John A. D. Aston, Davide Pigole

Proceedings of the 18th International Congress of Phonetic Sciences, 2015

2014

Reprint of "Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin".

Adam J. Hall, Michael J. Chappell, John A. D. Aston, Stephen A. Ward

Comput. Methods Programs Biomed., 2014

2013

Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin.

Adam J. Hall, Michael J. Chappell, John A. D. Aston, Stephen A. Ward

Comput. Methods Programs Biomed., 2013

2012

Implied distributions in multiple change point problems.

John A. D. Aston, Jyh-Ying Peng, Donald E. K. Martin

Stat. Comput., 2012

A Self-Organizing State-Space-Model Approach for Parameter Estimation in Hodgkin-Huxley-Type Models of Single Neurons.

Dimitrios V. Vavoulis, Volko A. Straub, John A. D. Aston, Jianfeng Feng

PLoS Comput. Biol., 2012

Detecting and estimating changes in dependent functional data.

John A. D. Aston, Claudia Kirch

J. Multivar. Anal., 2012

Bayesian model comparison via path-sampling sequential Monte Carlo.

Yan Zhou, Adam M. Johansen, John A. D. Aston

Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

2010

Linguistic and Human Effects on F₀ in a Tonal Dialect of Qiang.

Jonathan Evans, Man-ni Chu, John A. D. Aston, Chao-yu Su

Phonetica, 2010

2009

MR Image Segmentation Using a Power Transformation Approach.

Juin-Der Lee, Hong-Ren Su, Philip E. Cheng, Michelle Liou, John A. D. Aston, Arthur C. Tsai, Cheng-Yu Chen

IEEE Trans. Medical Imaging, 2009

Smoothing dynamic positron emission tomography time courses using functional principal components.

Ci-Ren Jiang, John A. D. Aston, Jane-Ling Wang

NeuroImage, 2009

2008

Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning.

Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng-Yuan Liou, John Ashburner

IEEE Trans. Medical Imaging, 2008

Waiting time distribution of generalized later patterns.

Donald E. K. Martin, John A. D. Aston

Comput. Stat. Data Anal., 2008

2007

Reproducibility Analysis of Event-Related fMRI Experiments Using Laguerre Polynomials.

Hong-Ren Su, Michelle Liou, Philip E. Cheng, John A. D. Aston, Shang-Hong Lai

Proceedings of the Neural Information Processing, 14th International Conference, 2007

2006

Multi-resolution Bayesian regression in PET dynamic studies using wavelets.

Federico E. Turkheimer, John A. D. Aston, Marie-Claude Asselin, Rainer Hinz

NeuroImage, 2006

A method for generating reproducible evidence in fMRI studies.

Michelle Liou, Hong-Ren Su, Juin-Der Lee, John A. D. Aston, Arthur C. Tsai, Philip E. Cheng

NeuroImage, 2006

2005

Wavelet variance components in image space for spatiotemporal neuroimaging data.

John A. D. Aston, Roger N. Gunn, Rainer Hinz, Federico E. Turkheimer

NeuroImage, 2005

2003

A Linear Wavelet Filter for Parametric Imaging with Dynamic PET.

Federico E. Turkheimer, John A. D. Aston, Richard B. Banati, Cyril Riddell, Vincent J. Cunningham

IEEE Trans. Medical Imaging, 2003

Dynamic functional changes associated with cognitive skill learning of an adapted version of the Tower of London task.

M. H. Beauchamp, Alain Dagher, John A. D. Aston, Julien Doyon

NeuroImage, 2003

2002

A General Statistical Analysis for fMRI Data.

Keith J. Worsley, C. H. Liao, John A. D. Aston, V. Petre, G. H. Duncan, F. Morales, Alan C. Evans

NeuroImage, 2002

Estimating the Delay of the fMRI Response.

C. H. Liao, Keith J. Worsley, Jean-Baptiste Poline, John A. D. Aston, G. H. Duncan, Alan C. Evans

NeuroImage, 2002