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Publications

Ebejer, J.-P. et al. (2019) “Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening”, Journal of Chemical Information and Modeling [Preprint].
Chan, L., Hutchison, G. and Morris, G. (2019) “Bayesian optimization for conformer generation”, Journal of Cheminformatics, 11(32).
Chan, L., Hutchison, G. and Morris, G. (2019) “Bayesian optimization for conformer generation”, Journal of Cheminformatics, 11(32).
Leung, S. et al. (2019) “SuCOS is better than RMSD for evaluating fragment elaboration and docking poses.”
Richards, D. and Rebeschini, P. (2019) “Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up”, arXiv.
Merel, J. et al. (2019) “Neural probabilistic motor primitives for humanoid control”, in International Conference on Learning Representations.
Nalisnick, E. et al. (2019) “Do deep generative models know what they don’t know?”, in International Conference on Learning Representations.
Zhou, Y. et al. (2019) “LF-PPL: A low-level first order probabilistic programming language for non-differentiable models”, in Proceedings of Machine Learning Research. ML Research Press, pp. 148–157.
Lee, J. et al. (2019) “A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure”, in Proceedings of Machine Learning Research. PMLR, pp. 758–767.
Hejblum, B. et al. (2019) “Sequential Dirichlet process mixtures of multivariate skew t-distributions for model-based clustering of flow cytometry data”, Annals of Applied Statistics, 13(1), pp. 638–660.