Brieuc Lehmann

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Citations	177	171
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Chris HolmesVerified email at stats.ox.ac.uk
Sylvia RichardsonDirector of MRC Biostatistics Unit and Professor of Biostatistics, University of CambridgeVerified email at mrc-bsu.cam.ac.uk
Ann-Marie MallonMRC HarwellVerified email at har.mrc.ac.uk
Peter J. DiggleDistinguished Professor, Lancaster UniversityVerified email at lancaster.ac.uk
Marta BlangiardoProfessor of Biostatistics, MRC Centre for Environment and Health, Imperial CollegeVerified email at imperial.ac.uk
Radka JersakovaThe Alan Turing InstituteVerified email at turing.ac.uk
Tullia PadelliniBank of ItalyVerified email at bancaditalia.it
George NicholsonOxford UniversityVerified email at stats.ox.ac.uk
Mark BriersAlan Turing InstituteVerified email at turing.ac.uk
Simon R WhiteSenior Investigator Statistician, Medical Research Council Biostatistics UnitVerified email at mrc-bsu.cam.ac.uk
Linda GeerligsAssociate professorVerified email at donders.ru.nl
Richard HensonMRC Cognition & Brain Sciences Unit, University of Cambridge, UKVerified email at mrc-cbu.cam.ac.uk
Fabian FalckUniversity of OxfordVerified email at stats.ox.ac.uk
Oscar ClivioPhD student, University of OxfordVerified email at spc.ox.ac.uk

Brieuc Lehmann

Statistical Science, University College London

Verified email at ucl.ac.uk - Homepage

Health equity Bayesian computation Polygenic risk scores Statistical network analysis


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Improving local prevalence estimates of SARS-CoV-2 infections using a causal debiasing framework G Nicholson, B Lehmann, T Padellini, KB Pouwels, R Jersakova, J Lomax, ... Nature Microbiology 7 (1), 97-107, 2022	34*	2022
Assessing dynamic functional connectivity in heterogeneous samples BCL Lehmann, SR White, RN Henson, L Geerligs NeuroImage 157, 635-647, 2017	29	2017
Characterising group-level brain connectivity: a framework using Bayesian exponential random graph models BCL Lehmann, RN Henson, L Geerligs, SR White NeuroImage 225, 2021	22	2021
Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: a population-based ecological study T Padellini, R Jersakova, PJ Diggle, C Holmes, RE King, BCL Lehmann, ... The Lancet Regional Health–Europe 15, 2022	20	2022
Learning from data with structured missingness R Mitra, SF McGough, T Chakraborti, C Holmes, R Copping, ... Nature Machine Intelligence 5 (1), 13-23, 2023	18	2023
Interoperability of statistical models in pandemic preparedness: principles and reality G Nicholson, M Blangiardo, M Briers, PJ Diggle, TE Fjelde, H Ge, ... Statistical science: a review journal of the Institute of Mathematical …, 2022	17	2022
Optimal strategies for learning multi-ancestry polygenic scores vary across traits B Lehmann, M Mackintosh, G McVean, C Holmes Nature Communications 14 (1), 4023, 2023	8*	2023
Neural score matching for high-dimensional causal inference O Clivio, F Falck, B Lehmann, G Deligiannidis, C Holmes International Conference on Artificial Intelligence and Statistics, 7076-7110, 2022	8	2022
A Predictive Approach to Bayesian Nonparametric Survival Analysis E Fong, B Lehmann International Conference on Artificial Intelligence and Statistics, 6990-7013, 2022	7	2022
Bayesian imputation of COVID-19 positive test counts for nowcasting under reporting lag R Jersakova, J Lomax, J Hetherington, B Lehmann, G Nicholson, M Briers, ... Journal of the Royal Statistical Society Series C: Applied Statistics 71 (4 …, 2022	6	2022
Inferring differences between networks using Bayesian exponential random graph models BCL Lehmann	4	2019
Bayesian exponential random graph models for populations of networks B Lehmann, S White arXiv preprint arXiv:2104.05110, 2021	3	2021
Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates S Ghalebikesabi, CC Holmes, E Fong, B Lehmann Uncertainty in Artificial Intelligence, 658-668, 2023	1	2023
Understanding COVID-19 testing behaviour in England through a sociodemographic lens S Bajaj, S Chen, R Creswell, R Naidoo, J L.-H. Tsui, O Kolade, ... medRxiv, 2023.10. 26.23297608, 2023		2023

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