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Welcome to The Centre for Probability, Statistics and Data Science

The centre covers three broadly overlapping main areas of research: probability, statistics and data science. Probability theory is a core topic within mathematics and a foundational aspect in much of the work of the centre. A broad range of areas within probability and applied probability are investigated from stochastic processes, understanding the properties of random mathematical structures including many applications to areas such as statistical physics, finance, etc. The centre also has a strong group of statisticians developing both statistical theory, e.g. Bayesian inference, methodologies, e.g. modelling of spatio-temporal data, and applications, e.g. biostatistics. Finally, the centre has in expertise of other aspects of data science including the foundations of machine learning, solving inverse systems as related to data, topological techniques, and others. 

News

Recent Publications

  • Lavigne A and Liverani S (2023). Quantifying the uncertainty of partitions for infinite mixture models. Statistics and Probability Letters, Elsevier 
    06-09-2023
  • Wilk M, Harper G, Firman N, Liverani S and Dezateux C (2023). OP140 Household associations between child and adult weight status in an ethnically diverse urban population: cross-sectional study using linked primary care and National Child Measurement Programme records. SSM Annual Scientific Meeting
    01-08-2023
  • Glau K and Wunderlich L (2023). Neural network expression rates and applications of the deep parametric PDE method in counterparty credit risk. Annals of Operations Research, Springer, 1-27.  
    13-04-2023

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