Publications

Ayed, F., Lee, J. and Caron, F. (2022) “The Normal-Generalised Gamma-Pareto process: a novel pure-jump Levy process with flexible tail and jump-activity properties”, Bayesian Analysis, 19(1), pp. 123–152.

Dupont, E. et al. (2022) “COIN++: neural compression across modalities”, Transactions on Machine Learning Research, 2022(11).

Crook, O. et al. (2022) “Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics.”, The annals of applied statistics, 16(4), pp. 22 - aoas1603.

Crook, O. et al. (2022) “Analysis of the first genetic engineering attribution challenge”, Nature Communications, 13(1), p. 7374.

Wu, F. and Rebeschini, P. (2022) “Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent”, Information and Inference: a Journal of the IMA, 12(2), pp. 633–713.

Teh, Y. et al. (2022) “Authors’ Reply to the Discussion of ‘Efficient Bayesian Inference of Instantaneous Reproduction Numbers at Fine Spatial Scales, with an Application to Mapping and Nowcasting the Covid-19 Epidemic in British Local Authorities’ by Teh et al. in Session 2 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 11 June 2021”, Journal of the Royal Statistical Society Series A (Statistics in Society), 185(Supplement_1), pp. s107 - s109.

Denholm, J. et al. (2022) “Multiple-instance-learning-based detection of coeliac disease in histological whole-slide images”, Journal of Pathology Informatics, 13.

Crook, O. et al. (2022) “Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE”, Nature Communications, 13(1), p. 5948.

Alfano, C. and Rebeschini, P. (2022) “Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization”, arXiv.

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