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Publications

Mitra, R. et al. (2023) “Learning from data with structured missingness”, Nature Machine Intelligence, 5(1), pp. 13–23.
Xu, J. et al. (2023) “Deep Stochastic Processes via Functional Markov Transition Operators”, in Advances in Neural Information Processing Systems.
Campbell, A. et al. (2023) “Trans-Dimensional Generative Modeling via Jump Diffusion Models”, in. Curran Associates, pp. 42217–42257.
Sharma, M. et al. (2023) “Do Bayesian Neural Networks Need To Be Fully Stochastic?”, in Proceedings of Machine Learning Research, pp. 7694–7722.
Miao, N. et al. (2023) “Learning Instance-Specific Augmentations by Capturing Local Invariances”, in Proceedings of Machine Learning Research, pp. 24720–24736.
Miao, N. et al. (2023) “Learning Instance-Specific Augmentations by Capturing Local Invariances”, in Proceedings of Machine Learning Research, pp. 24720–24736.
Ivanova, D. et al. (2023) “CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design”, in Proceedings of Machine Learning Research, pp. 14445–14464.
Venkatesh, S. et al. (2023) “The genetic architecture of changes in adiposity during adulthood”, medRxiv.
Venkatesh, S. et al. (2023) “The genetic architecture of changes in adiposity during adulthood”, medRxiv.
Bajaj, S. et al. (2023) “Understanding COVID-19 testing behaviour in England through a sociodemographic lens”, medRxiv.