John A. D. Aston

39 papers A 1Journal 35Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events. CoRR Yichen Kelly Chen, Sören Dittmer, Kinga Bernatowicz, Josep Arús-Pous, Kamen Bliznashki, John A. D. Aston, James H. F. Rudd, Carola-Bibiane Schönlieb, James Jones, Michael Roberts
2024	J	`jnl`	Recent methodological advances in federated learning for healthcare. Patterns Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie P. G. Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
2023	J	`jnl`	Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data. CoRR 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
2023	J	`jnl`	Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. 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 R. 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
2023	J	`jnl`	Recent Methodological Advances in Federated Learning for Healthcare. CoRR 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
2023	J	`jnl`	Reinterpreting survival analysis in the universal approximator age. CoRR Sören Dittmer, Michael Roberts, Jacobus Preller, AIX-COVNET Collaboration, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2022	J	`jnl`	Classification of datasets with imputed missing values: does imputation quality matter? CoRR 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
2022	J	`jnl`	Eigen-Adjusted Functional Principal Component Analysis. J. Comput. Graph. Stat. Ci-Ren Jiang, Eardi Lila, John A. D. Aston, Jane-Ling Wang
2022	J	`jnl`	Navigating the challenges in creating complex data systems: a development philosophy. CoRR 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
2022	J	`jnl`	On Krylov Methods for Large Scale CBCT Reconstruction. CoRR Malena Sabate Landman, Ander Biguri, Sepideh Hatamikia, Richard P. Boardman, John A. D. Aston, Carola-Bibiane Schönlieb
2022	J	`jnl`	Testing for Geometric Invariance and Equivariance. CoRR Louis G. Christie, John A. D. Aston
2020	J	`jnl`	A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis. SIAM J. Imaging Sci. Noémie Debroux, John A. D. Aston, Fabien Bonardi, Alistair Forbes, Carole Le Guyader, Marina Romanchikova, Carola-Bibiane Schönlieb
2019	J	`jnl`	A Variational Model Dedicated to Joint Segmentation, Registration and Atlas Generation for Shape Analysis. CoRR Noémie Debroux, John A. D. Aston, Fabien Bonardi, Alistair Forbes, Carole Le Guyader, Marina Romanchikova, Carola Schönlieb
2018	J	`jnl`	Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models. J. Mach. Learn. Res. Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf
2018	J	`jnl`	Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers. IEEE J. Sel. Top. Signal Process. Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf
2017	J	`jnl`	Gaussian tree constraints applied to acoustic linguistic functional data. J. Multivar. Anal. Nathaniel Shiers, John A. D. Aston, Jim Q. Smith, John S. Coleman
2017	A	`conf`	Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders. UAI Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf
2017	J	`jnl`	Veiled Attributes of the Variational Autoencoder. CoRR Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf
2015	—	`conf`	Reconstructing the sounds of words from the past. ICPhS John S. Coleman, John A. D. Aston, Davide Pigole
2015	J	`jnl`	The Uncertainty of Storm Season Changes: Quantifying the Uncertainty of Autocovariance Changepoints. Technometrics Christopher F. H. Nam, John A. D. Aston, Idris A. Eckley, Rebecca Killick
2014	J	`jnl`	Reprint of "Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin". Comput. Methods Programs Biomed. Adam J. Hall, Michael J. Chappell, John A. D. Aston, Stephen A. Ward
2013	J	`jnl`	Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin. Comput. Methods Programs Biomed. Adam J. Hall, Michael J. Chappell, John A. D. Aston, Stephen A. Ward
2012	J	`jnl`	A Self-Organizing State-Space-Model Approach for Parameter Estimation in Hodgkin-Huxley-Type Models of Single Neurons. PLoS Comput. Biol. Dimitrios V. Vavoulis, Volko A. Straub, John A. D. Aston, Jianfeng Feng
2012	—	`conf`	Bayesian model comparison via path-sampling sequential Monte Carlo. SSP Yan Zhou, Adam M. Johansen, John A. D. Aston
2012	J	`jnl`	Detecting and estimating changes in dependent functional data. J. Multivar. Anal. John A. D. Aston, Claudia Kirch
2012	J	`jnl`	Implied distributions in multiple change point problems. Stat. Comput. John A. D. Aston, Jyh-Ying Peng, Donald E. K. Martin
2010	J	`jnl`	Linguistic and Human Effects on F₀ in a Tonal Dialect of Qiang. Phonetica Jonathan Evans, Man-ni Chu, John A. D. Aston, Chao-yu Su
2009	J	`jnl`	MR Image Segmentation Using a Power Transformation Approach. IEEE Trans. Medical Imaging Juin-Der Lee, Hong-Ren Su, Philip E. Cheng, Michelle Liou, John A. D. Aston, Arthur C. Tsai, Cheng-Yu Chen
2009	J	`jnl`	Smoothing dynamic positron emission tomography time courses using functional principal components. NeuroImage Ci-Ren Jiang, John A. D. Aston, Jane-Ling Wang
2008	J	`jnl`	Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning. IEEE Trans. Medical Imaging Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng-Yuan Liou, John Ashburner
2008	J	`jnl`	Waiting time distribution of generalized later patterns. Comput. Stat. Data Anal. Donald E. K. Martin, John A. D. Aston
2007	—	`conf`	Reproducibility Analysis of Event-Related fMRI Experiments Using Laguerre Polynomials. ICONIP (1) Hong-Ren Su, Michelle Liou, Philip E. Cheng, John A. D. Aston, Shang-Hong Lai
2006	J	`jnl`	A method for generating reproducible evidence in fMRI studies. NeuroImage Michelle Liou, Hong-Ren Su, Juin-Der Lee, John A. D. Aston, Arthur C. Tsai, Philip E. Cheng
2006	J	`jnl`	Multi-resolution Bayesian regression in PET dynamic studies using wavelets. NeuroImage Federico E. Turkheimer, John A. D. Aston, Marie-Claude Asselin, Rainer Hinz
2005	J	`jnl`	Wavelet variance components in image space for spatiotemporal neuroimaging data. NeuroImage John A. D. Aston, Roger N. Gunn, Rainer Hinz, Federico E. Turkheimer
2003	J	`jnl`	A Linear Wavelet Filter for Parametric Imaging with Dynamic PET. IEEE Trans. Medical Imaging Federico E. Turkheimer, John A. D. Aston, Richard B. Banati, Cyril Riddell, Vincent J. Cunningham
2003	J	`jnl`	Dynamic functional changes associated with cognitive skill learning of an adapted version of the Tower of London task. NeuroImage Miriam H. Beauchamp, Alain Dagher, John A. D. Aston, Julien Doyon
2002	J	`jnl`	A General Statistical Analysis for fMRI Data. NeuroImage Keith J. Worsley, C. H. Liao, John A. D. Aston, V. Petre, G. H. Duncan, F. Morales, Alan C. Evans
2002	J	`jnl`	Estimating the Delay of the fMRI Response. NeuroImage C. H. Liao, Keith J. Worsley, Jean-Baptiste Poline, John A. D. Aston, G. H. Duncan, Alan C. Evans