All Outputs (2)

JUNE: open-source individual-based epidemiology simulation (2021)
Journal Article
Aylett-Bullock, J., Cuesta-Lazaro, C., Quera-Bofarull, A., Icaza-Lizaola, M., Sedgewick, A., Truong, H., …Krauss, F. (2021). JUNE: open-source individual-based epidemiology simulation. Royal Society Open Science, 8(7), https://doi.org/10.1098/rsos.210506

We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic i... Read More about JUNE: open-source individual-based epidemiology simulation.

Efficient exploration and calibration of a semi-analytical model of galaxy formation with deep learning (2021)
Journal Article
Elliott, E. J., Baugh, C. M., & Lacey, C. G. (2021). Efficient exploration and calibration of a semi-analytical model of galaxy formation with deep learning. Monthly Notices of the Royal Astronomical Society, 506(3), 4011-4030. https://doi.org/10.1093/mnras/stab1837

We implement a sample-efficient method for rapid and accurate emulation of semi-analytical galaxy formation models over a wide range of model outputs. We use ensembled deep learning algorithms to produce a fast emulator of an updated version of the G... Read More about Efficient exploration and calibration of a semi-analytical model of galaxy formation with deep learning.