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Publications

Simsekli, U. et al. (2020) “Fractional underdamped langevin dynamics: Retargeting SGD with momentum under heavy-tailed gradient noise”, in 37th International Conference on Machine Learning, ICML 2020, pp. 8917–8927.
Bhatia, S. et al. (2020) “Estimating the number of undetected COVID-19 cases among travellers from mainland China.”, Wellcome open research, 5, pp. 143 – 143.
Ainslie, K. et al. (2020) “Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment.”
Richards, D., Rebeschini, P. and Rosasco, L. (2020) “Decentralised learning with distributed gradient descent and random features”, in 37th International Conference on Machine Learning Icml 2020, pp. 8075–8085.
Ramisch, A. et al. (2020) “Temporal variation of regulatory organization based on longitudinal RNA-seq data in twins”, in EUROPEAN JOURNAL OF HUMAN GENETICS, pp. 729–730.
Ainslie, K. et al. (2020) “Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment”, Wellcome open research, 5, pp. 81 – 81.
Camuto, A. et al. (2020) “Explicit regularisation in Gaussian noise injections”, in Advances in Neural Information Processing Systems.
Dorigatti, I. et al. (2019) “Risk of yellow fever virus importation into the United States from Brazil, outbreak years 2016–2017 and 2017–2018”, Scientific Reports, 9.
Vaškevičius, T., Kanade, V. and Rebeschini, P. (2019) “Implicit regularization for optimal sparse recovery”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Neural Information Processing Systems Foundation, pp. 2968–2979.
Teh, Y., Dupont, E. and Doucet, A. (2019) “Augmented neural ODEs”, Proceedings of the 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition (EMC2-NIPS 2019), 32(2019), pp. 1–11.