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Publications

Sharma, M. et al. (2020) “How robust are the estimated effects of nonpharmaceutical interventions against COVID-19?”, in Advances in Neural Information Processing Systems.
Lee, J. et al. (2020) “Bootstrapping neural processes”, in Advances in Neural Information Processing Systems.
He, B., Lakshminarayanan, B. and Teh, Y. (2020) “Bayesian deep ensembles via the neural tangent kernel”, in Advances in Neural Information Processing Systems.
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.
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.
Camuto, A. et al. (2020) “Explicit regularisation in Gaussian noise injections”, in Advances in Neural Information Processing Systems.
Zhou, Y. et al. (2020) “Divide, conquer, and combine: A new inference strategy for Probabilistic Programs with Stochastic Support”, 37th International Conference on Machine Learning, ICML 2020, PartF168147-15, pp. 11471–11482.
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.