Staff profile

Journal Article

• Proposer of the vote of thanks and contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’
  Wilkinson, D. (2024). Proposer of the vote of thanks and contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’. Journal of the Royal Statistical Society: Series B, 86(2), 302-304. https://doi.org/10.1093/jrsssb/qkad160
• Emulating long-term weather-driven transportation earthworks deterioration models to support asset management
  Helm, P., Svalova, A., Morsy, A., Rouainia, M., Smith, A., El-Hamalawi, A., Wilkinson, D., Postill, H., & Glendinning, S. (2024). Emulating long-term weather-driven transportation earthworks deterioration models to support asset management. Transportation Geotechnics, 44, Article 101155. https://doi.org/10.1016/j.trgeo.2023.101155
• A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields
  Johnson, S. R., Heaps, S. E., Wilson, K. J., & Wilkinson, D. J. (2023). A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields. Environmetrics, 34(8), https://doi.org/10.1002/env.2824
• A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant
  Hannaford, N., Heaps, S., Nye, T., Curtis, T., Allen, B., Golightly, A., & Wilkinson, D. (2023). A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant. Computational Statistics & Data Analysis, 179, https://doi.org/10.1016/j.csda.2022.107659
• MGnify: the microbiome sequence data analysis resource in 2023
  Richardson, L., Allen, B., Baldi, G., Beracochea, M., Bileschi, M., Burdett, T., Burgin, J., Caballero-Pérez, J., Cochrane, G., Colwell, L., Curtis, T., Escobar-Zepeda, A., Gurbich, T., Kale, V., Korobeynikov, A., Raj, S., Rogers, A., Sakharova, E., Sanchez, S., Wilkinson, D., & Finn, R. (2023). MGnify: the microbiome sequence data analysis resource in 2023. Nucleic Acids Research, 51(D1), D753-D759. https://doi.org/10.1093/nar/gkac1080
• Emulating computer experiments of transport infrastructure slope stability using Gaussian processes and Bayesian inference
  Svalova, A., Helm, P., Prangle, D., Rouainia, M., Glendinning, S., & Wilkinson, D. J. (2021). Emulating computer experiments of transport infrastructure slope stability using Gaussian processes and Bayesian inference. Data-Centric Engineering, 2, Article e12. https://doi.org/10.1017/dce.2021.14