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Efficient inversion strategies for estimating optical properties with Monte Carlo radiative transport models (2020)
Journal Article
Macdonald, C. M., Arridge, S., & Powell, S. (2020). Efficient inversion strategies for estimating optical properties with Monte Carlo radiative transport models. Journal of Biomedical Optics, 25(08), https://doi.org/10.1117/1.jbo.25.8.085002

Significance: Indirect imaging problems in biomedical optics generally require repeated evaluation of forward models of radiative transport, for which Monte Carlo is accurate yet computationally costly. We develop an approach to reduce this bottlene... Read More about Efficient inversion strategies for estimating optical properties with Monte Carlo radiative transport models.

Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom (2018)
Journal Article
Figueredo, G. P., Agrawal, U., Mase, J., Mesgarpour, M., Wagner, C., Soria, D., …John, R. (2019). Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems, 20(9), 3324-3336. https://doi.org/10.1109/TITS.2018.2875343

Although driving behaviour has been largely studied amongst private motor vehicles drivers, the literature addressing heavy goods vehicle (HGV) drivers is scarce. Identifying the existing groups of driving stereotypes and their proportions enables re... Read More about Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom.

Hyper-heuristics: theory and applications (2018)
Book
Pillay, N., & Qu, R. (2018). Hyper-heuristics: theory and applications. Cham, Switzerland: Springer Nature. doi:10.1007/978-3-319-96514-7

This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, pro... Read More about Hyper-heuristics: theory and applications.

Model checking for Coalition Announcement Logic (2018)
Conference Proceeding
Galimullin, R., Alechina, N., & van Ditmarsch, H. (2018). Model checking for Coalition Announcement Logic. In F. Trollmann, & A. Turhan (Eds.), KI 2018: Advances in Artificial Intelligence, 41st German Conference on AI, Berlin, Germany, September 24–28, 2018, Proceedings (11-23). https://doi.org/10.1007/978-3-030-00111-7_2

Coalition Announcement Logic (CAL) studies how a group of agents can enforce a certain outcome by making a joint announcement, regardless of any announcements made simultaneously by the opponents. The logic is useful to model imperfect information ga... Read More about Model checking for Coalition Announcement Logic.