Publications by Statistical Genetics and Epidemiology

Our research spans areas of statistical genetics, in particular the development of powerful statistical approaches to analyse genetic data, as well as studying infectious diseases.

Venkatesh, S. et al. (2023) “The genetic architecture of changes in adiposity during adulthood”, medRxiv.

Williams, C. et al. (2023) “A Unified Framework for U-Net Design and Analysis”, in Advances in Neural Information Processing Systems.

Mitra, R. et al. (2023) “Learning from data with structured missingness”, Nature Machine Intelligence, 5(1), pp. 13–23.

Hu, S. et al. (2023) “Leveraging fine-scale population structure reveals conservation in genetic effect sizes between human populations across a range of human phenotypes”, bioRxiv.

Shi, S. et al. (2023) “A Genomics England haplotype reference panel and the imputation of the UK Biobank”, medRxiv.

Giner-Sorolla, R. and Myers, S. (2023) “On cooperative libertines and wicked puritans”, Behavioral and Brain Sciences, 46, p. e306.

Ghalebikesabi, S. et al. (2023) “Quasi-Bayesian Nonparametric Density Estimation via Autoregressive Predictive Updates”, in Proceedings of Machine Learning Research, pp. 658–668.

Jewson, J., Ghalebikesabi, S. and Holmes, C. (2023) “Differentially Private Statistical Inference through β-Divergence One Posterior Sampling”, in Advances in Neural Information Processing Systems.

Bajaj, S. et al. (2023) “Understanding COVID-19 testing behaviour in England through a sociodemographic lens”, medRxiv.

Martin, N. et al. (2022) “A graph based neural network approach to immune profiling of multiplexed tissue samples”, pp. 3063–3067.