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Publications

Vales, S. et al. (2023) “Discovery and pharmacophoric characterization of chemokine network inhibitors using phage-display, saturation mutagenesis and computational modelling”, Nature Communications, 14(1).
Lu, X., Rainforth, T. and Teh, Y. (2023) “Daisee: Adaptive importance sampling by balancing exploration and exploitation”, Scandinavian Journal of Statistics, 50(3), pp. 1298–1324.
Lu, X., Rainforth, T. and Teh, Y. (2023) “Daisee: Adaptive importance sampling by balancing exploration and exploitation”, Scandinavian Journal of Statistics, 50(3), pp. 1298–1324.
Klarner, L., Rudner, T. and Morris, G. (2023) “Drug discovery under covariate shift with domain-informed prior distributions over functions”, in Krause, A. et al. (eds.). Journal of Machine Learning Research, pp. 17176–17197.
Whitehead, M. et al. (2023) “Making the invisible visible: what can we do about biased AI in medical devices?”, The BMJ, 382, pp. p1893 - p1893-.
Buttenschoen, M., Morris, G. and Deane, C. (2023) “PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences”, arXiv.
Klarner, L. et al. (2023) “Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions”, arXiv.
Klarner, L. et al. (2023) “Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions”, arXiv.
Armbruster, S. and Reinert, G. (2023) “COVID-19 incidence in the Republic of Ireland: A case study for network-based time series models.”
Lehmann, B. et al. (2023) “Optimal strategies for learning multi-ancestry polygenic scores vary across traits”, Nature Communications, 14(1), pp. 4023–4023.