Publications
Here is a selection of our recent publications.
2021
Active Latent Space Shape Model: A Bayesian Treatment of Shape Model Adaptation with an Application to Psoriatic Arthritis Radiographs,
Adwaye Rambojun, William Tillett, Tony Shardlow and Neill D. F. Campbell,
IEEE Winter Conf. on the Applications of Computer Vision (WACV), 2021
Black-Box Density Function Estimation using Recursive Partitioning,
Erik Bodin, Zhenwen Dai, Neill D. F. Campbell and Carl Henrik Ek,
Int. Conf. on Machine Learning (ICML), 2021
Inexact Derivative-Free Optimization for Bilevel Learning,
M. J. Ehrhardt and L. Roberts,
Journal of Mathematical Imaging and Vision vol. 63, no. 5, 2021
Chaos on Compact manifolds: Differentiable synchronisations beyond the Takens Theorem ,
Lyudmila Grigoryeva, Allen Hart, Juan-Pablo Ortega,
Physical Review E, 103, 062204, 2021
Echo state networks trained by Tikhonov least squares are L2 approximators of ergodic dynamical systems ,
A.G. Hart, J.L. Hook and J.H.P. Dawes,
Physica D vol. 421, 132882, 2021
A wavelet-based approach for imputation in nonstationary multivariate time series,
R Wilson, I Eckley, M Nunes and T Park,
Statistics and Computing, vol. 31, no. 2, 2021
Detecting changes in mean in the presence of time-varying autocovariance,
E McGonigle, R Killick and M Nunes,
Stat, vol. 10, no. 1, 2021
An MBO scheme for clustering and semi-supervised clustering of signed networks,
Mihai Cucuringu, Andrea Pizzoferrato, and Yves van Gennip,
Commun. Math. Sci. Vol. 19, No. 1, pp. 73–109, 2021
Multiple changepoint estimation in high-dimensional gaussian graphical models,
Gibberd Alex & Roy Sandipan,
In submission, 2021
Hedging parameter selection for basis pursuit,
S Chretien, A Gibberd and S Roy,
In submission, 2021
Inference of tissue relative proportions of the breast epithelial cell types luminal progenitor, basal, and luminal mature,
TE Bartlett, S Chandna and S Roy,
In submission, 2021
A rare-event study of frequency regulation and contingency services from grid-scale batteries,
Maldon P. Goodridge, John Moriarty, Andrea Pizzoferrato,
Phil. Trans. R. Soc. A 379: 20190433, 2021
Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?,
Konstantinos Katsikopoulos, Özgür Şimşek, Marcus Buckmann, Gerd Gigerenzer,
International Journal of Forecasting, 2021
Tensor decomposition methods for high-dimensional Hamilton-Jacobi-Bellman equations,
Sergey Dolgov, Dante Kalise, and Karl Kunisch,
SIAM J. Sci. Comput., 43(3), A1625-A1650, 2021
Iteratively Reweighted FGMRES and FLSQR for Sparse Reconstruction,
S. Gazzola, J. Nagy, M. Sabaté Landman,
SIAM Journal on Scientific Computing, S47-S69, 2021
2020
“Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations",
“D. Chen, M. Davies, and M. Golbabaee",
“International conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) vol.12262, https://doi.org/10.1007/978-3-030-59713-9_2", 2020
“Compressive MRI quantification using convex spatiotemporal priors and deep auto-encoders",
“M. Golbabaee, G. Bounincontri, C. Pirkl, et al.",
“arxiv preprint", 2020
Making decisions on subjective data: Aligning statistics with science to improve outcomes on the modified Irwin test,
Karen Tse, Oscar Hammar and Beate Ehrhardt,
Journal of Pharmacological and Toxicological Methods vol. 99, no. 106595, 2020
Accelerating Variance-Reduced Stochastic Gradient Methods,
Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb,
Mathematical Programming, https://doi.org/10.1007/s10107-020-01566-2, 2020
Compositional Uncertainty in Deep Gaussian Processes,
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell and Carl Henrik Ek,
Conf. on Uncertainty in Artificial Intelligence (UAI), 2020
Modulating Surrogates for Bayesian Optimization,
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill D. F. Campbell and Carl Henrik Ek,
Int. Conf. on Machine Learning (ICML), 2020
Monotonic Gaussian Process Flow,
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek and Neill D. F. Campbell,
Int. Conf. on Artificial Intelligence and Statistics (AISTATS), 2020
Robust Image Reconstruction with Misaligned Structural Information,
L. Bungert and M. J. Ehrhardt,
IEEE Access vol. 8, 2020
Learning the Sampling Pattern for MRI,
F. Sherry, M. Benning, J. C. De los Reyes, M. J. Graves, G. Maierhofer, G. Williams, C.-B. Schönlieb and M. J. Ehrhardt,
IEEE Transactions on Medical Imaging vol. 39, no. 12, 2020
Embedding and approximation theorems for echo state networks,
A.G. Hart, J.L. Hook and J.H.P. Dawes,
Neural Networks vol. 128, 234-247, 2020
Semi-automated simultaneous predictor selection for Regression-SARIMA models,
A Lowther, P Fearnhead, M Nunes and K Jensen,
Statistics and Computing, vol. 30, no. 2, 2020
Interpretable brain age prediction using linear latent variable models of functional connectivity,
R Monti, A Gibberd, S Roy, M Nunes, R Lorenz, R Leech, T Ogawa, M Kawanabe and A Hyvarinen,
PLOS One, vol. 15, no. 6, 2020
Generalised Network AutoRegressive Processes and the GNAR package,
M Knight, K Leeming, G Nason, M Nunes,
Journal Of Statistical Software, vol. 96, no. 5, 2020
Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary time series,
R Wilson, I Eckley, M Nunes and T Park,
Journal Of Statistical Software, vol. 96, no. 5, 2020
Classification in the wild: The art and science of transparent decision making,
Konstantinos Katsikopoulos, Özgür Şimşek, Marcus Buckmann, Gerd Gigerenzer” Publisher: “MIT Press,
, 2020
Consistent Multiple Changepoint Estimation with Fused Gaussian Graphical Models,
Gibberd Alex and Roy Sandipan,
Annals of the Institute of Statistical Mathematics, 2020
Deep composition of Tensor Trains using squared inverse Rosenblatt transports,
Tiangang Cui and Sergey Dolgov,
arXiv preprint 2007.06968, 2020
Approximation and sampling of multivariate probability distributions in the tensor train decomposition,
Sergey Dolgov, Karim Anaya-Izquierdo, Colin Fox and Robert Scheichl,
Statistics and Computing 30: 603-625, 2020
Krylov methods for inverse problems: Surveying classical, and introducing new, algorithmic approaches,
S. Gazzola, M. Sabaté Landman,
GAMM‐Mitteilungen 43 (4), e202000017, 2020
2019
Approximate Bayesian Inference for Geostatistical Generalised Linear Models,
Evangelos Evangelou,
Foundations of Data Science, 2019
An innovative non-invasive technique for subcutaneous tumour measurements,
Juan Delgado San Martin, Beate Ehrhardt, Marcin Paczkowski, Sean Hackett, Andrew Smith, Wajahat Waraich, James Klatzow, Adeala Zabair, Anna Chabokdast, Leonardo Rubio-Navarro, Amar Rahi, and Zena Wilson,
PLoS ONE vol. 14, no. 10, 2019
Network modularity in the presence of covariates,
Beate Ehrhardt and Patrick J Wolfe,
SIAM Rev., 2019
Development of an automated segmentation algorithm to identify bones of the hand,
A.M. Rambojun, W. Tillett, N.D.F. Campbell, and T. Shardlow,
Annals of the Rheumatic Diseases, vol. 78., 2019
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models,
T. Deveney, E. Mueller, and T. Shardlow,
arXiv e-print 1910.01547, 2019
Max-plus Linear Inverse Problems: 2-norm regression and system identification of max-plus linear dynamical systems with Gaussian noise,
J. Hook,
arXiv e-prints, 2019
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures,
Andrew Lawrence, Carl Henrik Ek and Neill D. F. Campbell,
Int. Conf. on Machine Learning (ICML), 2019
Gaussian Process Latent Variable Alignment Learning,
Ieva Kazlauskaite, Carl Henrik Ek and Neill D. F. Campbell,
Int. Conf. on Artificial Intelligence and Statistics (AISTATS), 2019
Regularization in directable environments with application to Tetris,
“Jan Malte Lichtenberg, Özgür Şimşek”,
“ICML", 2019
Long memory estimation for complex-valued time series,
M Knight and M Nunes,
Statistics and Computing, vol. 29, no. 1, 2019
2018
Bridging trees for posterior inference on ancestral recombination graphs,
K. Heine, A. Beskos, A. Jasra, D. Balding and M. De Iorio,
Proc. Math. Phys. Eng. Sci. vol. 474, no. 2220, 2018
A domain specific language for performance portable molecular dynamics algorithms,
William Robert Saunders, James Grant and Eike Hermann Müller,
Comput. Phys. Commun. vol. 224, 2018
A stratified age-period-cohort model for spatial heterogeneity in all-cause mortality,
Theresa Smith,
arXiv e-print 1806.02748, 2018
A low-rank approach to the solution of weak constraint variational data assimilation problems,
Melina A Freitag and Daniel L H Green,
J. Comput. Phys. vol. 357, 2018
Likelihood Inference for Large Scale Stochastic Blockmodels With Covariates Based on a Divide-and-Conquer Parallelizable Algorithm With Communication,
Sandipan Roy, Yves Atchadé and George Michailidis,
J. Comput. Graph. Stat., 2018
Balanced model order reduction for linear random dynamical systems driven by Lévy noise,
Martin Redmann and Melina A Freitag,
Journal of Computational Dynamics vol. 5, no. 1&2, 2018
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications,
A. Chambolle, M. Ehrhardt, P. Richtárik and C. Schönlieb,
SIAM J. Optim., 2018
Inexact Gradient Projection and Fast Data Driven Compressed Sensing,
M. Golbabaee and M. E. Davies,
IEEE Trans. Inf. Theory vol. 64, no. 10, 2018
Dirichlet process Gaussian-mixture model: An application to localizing coalescing binary neutron stars with gravitational-wave observations,
W. Del Pozzo, C. P. L. Berry, A. Ghosh, T. S. F. Haines and others,
Mon. Not. R. Astron. Soc., 2018
Multilevel Monte Carlo and Improved Timestepping Methods in Atmospheric Dispersion Modelling,
Grigoris Katsiolides, Eike H. Mueller, Robert Scheichl, Tony Shardlow, Michael B. Giles and David J. Thomson,
J. Computational Physics vol. 354, 2018
Support Localization and the Fisher Metric for off-the-grid Sparse Regularization,
Clarice Poon, Nicolas Keriven and Gabriel Peyré,
arXiv e-print 1810.03340, 2018
Reconstructing Networks with Unknown and Heterogeneous Errors,
Tiago P Peixoto,
Phys. Rev. X vol. 8, no. 4, 2018
Sequence Alignment with Dirichlet Process Mixtures,
Ieva Kazlauskaite, Ivan Ustyuzhaninov, Carl Henrik Ek and Neill D. F. Campbell,
NeurIPS Workshop on Bayesian Non-Parametrics, 2018
Structured Uncertainty Prediction Networks,
Garoe Dorta Perez, Sara Vicente, Lourdes Agapito, Neill D. F. Campbell and Ivor Simpson,
IEEE Conf.~on Computer Vision and Pattern Recognition (CVPR), 2018
Complex-valued wavelet lifting and applications,
M Knight and M Nunes,
Technometrics, vol. 60, no. 1, 2018
2017
Sequential empirical Bayes method for filtering dynamic spatiotemporal processes,
Evangelos Evangelou and Vasileios Maroulas,
Spatial Statistics vol. 21, 2017
Multivariate locally stationary 2D wavelet processes with application to colour texture analysis,
Sarah L Taylor, Idris A Eckley and Matthew A Nunes,
Stat. Comput. vol. 27, no. 4, 2017
Fluctuations, stability and instability of a distributed particle filter with local exchange,
Kari Heine and Nick Whiteley,
Stochastic Process. Appl. vol. 127, no. 8, 2017
Change point estimation in high dimensional Markov random-field models,
Sandipan Roy, Yves Atchadé and George Michailidis,
J. R. Stat. Soc. Series B Stat. Methodol. vol. 79, no. 4, 2017
Max-Plus Algebraic Statistical Leverage Scores,
J. Hook,
SIAM Journal on Matrix Analysis and Applications vol. 38, no. 4, 2017
Langevin equations for landmark image registration with uncertainty,
Stephen Marsland and Tony Shardlow,
SIAM Imaging Science vol. 10, 2017
Breaking the coherence barrier: a new theory for compressed sensing,
Ben Adcock, Anders C Hansen, Clarice Poon and Bogdan Roman,
Forum of Mathematics, Sigma vol. 5, 2017
Towards the Geometry of Model Sensitivity: An Illustration,
Karim Anaya-Izquierdo, Frank Critchley, Paul Marriott and Paul Vos,
Computational Information Geometry: For Image and Signal Processing, 2017
Latent Gaussian Process Regression,
Erik Bodin, Neill D. F. Campbell and Carl Henrik Ek,
arXiv e-print 1707.05534, 2017
Latent Structure Learning using Gaussian and Dirichlet Processes,
Andrew Lawrence, Carl Henrik Ek and Neill D. F. Campbell,
NeurIPS Workshop on Advances in Modelling and Learning Interactions from Complex Data, 2017
A wavelet lifting approach to long-memory estimation,
M Knight, G Nason and M Nunes,
Statistics and Computing, vol. 27, no. 6, 2017
2016
Statistical Inference, Learning and Models in Big Data,
Beate Franke, Jean-François Plante, Ribana Roscher, En-Shiun Annie Lee, Cathal Smyth, Armin Hatefi, Fuqi Chen, Einat Gil, Alexander Schwing, Alessandro Selvitella, Michael M Hoffman, Roger Grosse, Dieter Hendricks and Nancy Reid,
Int. Stat. Rev. vol. 84, no. 3, 2016
Why most decisions are easy in tetris-and perhaps in other sequential decision problems, as well,
Özgür Şimşek, Simon Algorta and Amit Kothiyal,
Proceedings of Machine Learning Research vol. 48, 2016
2015
Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model,
Jonathan W Bartlett, Shaun R Seaman, Ian R White, James R Carpenter and Alzheimer's Disease Neuroimaging Initiative,
Stat. Methods Med. Res. vol. 24, no. 4, 2015
Modelling and Prediction of Time Series Arising on a Graph,
Matthew A Nunes, Marina I Knight and Guy P Nason,
Modeling and Stochastic Learning for Forecasting in High Dimensions, 2015
Restricted Covariance Priors with Applications in Spatial Statistics,
Theresa R Smith, Jon Wakefield and Adrian Dobra,
Bayesian Anal. vol. 10, no. 4, 2015
Model selection with low complexity priors,
Samuel Vaiter, Mohammad Golbabaee, Jalal Fadili and Gabriel Peyré,
Inf Inference vol. 4, no. 3, 2015
2014
Improving upon the efficiency of complete case analysis when covariates are MNAR,
Jonathan W Bartlett, James R Carpenter, Kate Tilling and Stijn Vansteelandt,
Biostatistics vol. 15, no. 4, 2014
Alternating Minimal Energy Methods for Linear Systems in Higher Dimensions,
S. Dolgov and D. Savostyanov,
SIAM J. Sci. Comput. vol. 36, no. 5, 2014
Joint reconstruction of PET-MRI by exploiting structural similarity,
Matthias J Ehrhardt, Kris Thielemans, Luis Pizarro, David Atkinson, Sébastien Ourselin, Brian F Hutton and Simon R Arridge,
Inverse Probl. vol. 31, no. 1, 2014
Massively parallel solvers for elliptic partial differential equations in numerical weather and climate prediction,
E H Müller and R Scheichl,
Quarterly Journal of the Royal, 2014
Active Rare Class Discovery and Classification Using Dirichlet Processes,
Tom S F Haines and Tao Xiang,
Int. J. Comput. Vis. vol. 106, no. 3, 2014
Hierarchical Block Structures and High-Resolution Model Selection in Large Networks,
Tiago P Peixoto,
Phys. Rev. X vol. 4, no. 1, 2014
2013
Linear decision rule as aspiration for simple decision heuristics,
Özgür Şimşek,
Advances in Neural Information Processing Systems 26, 2013
Computational Information Geometry in Statistics: Foundations,
Karim Anaya-Izquierdo, Frank Critchley, Paul Marriott and Paul Vos,
Lecture Notes in Computer Science, 2013