Mathematical Institute

Learning to Adapt - Personalising Cancer Treatment Schedules using Deep Reinforcement Learning

One of the greatest challenges in cancer treatment is maximising the response to a given drug - how can doctors get the greatest impact for the patient from the drug?

Traditionally, the answer to this has been ‘maximum tolerated dose’ (MTD) therapy, where the patient continually receives a high drug dose, with no breaks in treatment.

MCGAN: Enhancing GAN Training with Regression-Based Generator Loss

Xiao, B Ni, H Yang, W (27 May 2024) http://arxiv.org/abs/2405.17191v3

The AdS Veneziano amplitude at small curvature

Alday, L Chester, S Hansen, T Zhong, D Journal of High Energy Physics volume 2024 issue 5 (29 May 2024)

Local dominance unveils clusters in networks

Shi, D Shang, F Chen, B Expert, P Lü, L Stanley, H Lambiotte, R Evans, T Li, R Communications Physics volume 7 issue 1 (31 May 2024)

Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution

Yang, J Heinrich, T Winkler, J Lafond, F Koutroumpis, P Farmer, J Industrial and Corporate Change dtae021 (31 May 2024)

Examples of topologically unknotted tori

Juhasz, A Powell, M Transactions of the American Mathematical Society volume 11 issue 37 1266-1293 (06 Nov 2024)

Optimal control of collective electrotaxis in epithelial monolayers

Martina-Perez, S Breinyn, I Cohen, D Baker, R Bulletin of Mathematical Biology volume 86 issue 8 (19 Jun 2024)

Typical Ramsey properties of the primes, abelian groups and other
discrete structures

Freschi, A Hancock, R Treglown, A (29 May 2024) http://arxiv.org/abs/2405.19113v2

On solution-free sets of integers

Hancock, R Treglown, A (28 Jul 2016) http://arxiv.org/abs/1607.08399v2

On solution-free sets of integers II

Hancock, R Treglown, A (25 Nov 2016) http://arxiv.org/abs/1611.08498v2

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