Publications

Ter-Minassian, L. et al. (2023) “PWSHAP: a path-wise explanation model for targeted variables”, in Proceedings of the 40th International Conference on Machine Learning. Proceedings of Machine Learning Research, pp. 34054–34089.

Caron, F., Panero, F. and Rousseau, J. (2023) “On sparsity, power-law and clustering properties of graphex processes”, Advances in Applied Probability, 55(4), pp. 1211–1253.

Sinha, S. et al. (2023) “Comparison of machine learning techniques in prediction of mortality following cardiac surgery: analysis of over 220 000 patients from a large national database”, European Journal of Cardio-Thoracic Surgery, 63(6), p. ezad183.

Holmes, C. and Walker, S. (2023) “Statistical inference with exchangeability and martingales”, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, 381(2247), p. 20220143.

Dunger‐Baldauf, C. et al. (2023) “Generating the Right Evidence at the Right Time: Principles of a New Class of Flexible Augmented Clinical Trial Designs”, Clinical Pharmacology & Therapeutics, 113(5), pp. 1132–1138.

Lee, J., Miscouridou, X. and Caron, F. (2023) “A unified construction for series representations and finite approximations of completely random measures”, Bernoulli, 29(3), pp. 2142–2166.

Falck, F. et al. (2023) “A multi-resolution framework for U-nets with applications to hierarchical VAEs”, in Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Curran Associates, pp. 15529–15544.

De Bortoli, V. et al. (2023) “Riemannian score-based generative modelling”, in Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Curran Associates, pp. 2406–2422.

Naik, C. et al. (2023) “Bayesian Nonparametrics for Sparse Dynamic Networks”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Nature, pp. 191–206.