Dr Michael Smith

Journal articles

• Yao M, Smith M & Peng C (2025) Modelling the effects of vegetation and urban form on air quality in real urban environments: A systematic review of measurements, methods, and predictions. Urban Forestry & Urban Greening, 105. View this article in WRRO
• Chapman KE, Smith MT, Gaston KJ & Hempel de Ibarra N (2024) Bumblebee nest departures under low light conditions at sunrise and sunset. Biology Letters, 20(4). View this article in WRRO
• Smith MT, Ross M, Ssematimba J, Álvarez MA, Bainomugisha E & Wilkinson R (2023) Modelling calibration uncertainty in networks of environmental sensors. Journal of the Royal Statistical Society Series C: Applied Statistics, 72(5), 1187-1209. View this article in WRRO
• Smith MT, Grosse K, Backes M & Álvarez MA (2023) Adversarial vulnerability bounds for Gaussian process classification. Machine Learning, 112(3), 971-1009. View this article in WRRO
• Smith MT, Livingstone M & Comont R (2021) A method for low‐cost, low‐impact insect tracking using retroreflective tags. Methods in Ecology and Evolution, 12(11), 2184-2195.
• Smith MT, Alvarez MA & Lawrence ND (2021) Differentially private regression and classification with sparse Gaussian processes. Journal of Machine Learning Research, 22. View this article in WRRO
• Fotheringham J, Smith MT, Froissart M, Kronenberg F, Stenvinkel P, Floege J, Eckardt K-U & Wheeler DC (2020) Hospitalization and mortality following non-attendance for hemodialysis according to dialysis day of the week : a European cohort study. BMC Nephrology, 21(1). View this article in WRRO
• Smith MT, Zwiessele M & Lawrence ND (2016) Differentially Private Gaussian Processes.. CoRR, abs/1606.00720.
• Bett D, Stevenson CH, Shires KL, Smith MT, Martin SJ, Dudchenko PA & Wood ER (2013) The Postsubiculum and Spatial Learning: The Role of Postsubicular Synaptic Activity and Synaptic Plasticity in Hippocampal Place Cell, Object, and Object-Location Memory. The Journal of Neuroscience, 33(16), 6928-6943.
• Feldwisch-Drentrup H, Barrett AB, Smith MT & van Rossum MCW (2012) Fluctuations in the open time of synaptic channels: An application to noise analysis based on charge. Journal of Neuroscience Methods, 210(1), 15-21.
• Wutte M () Physiological signal variability in hMT+ reflects performance on a direction discrimination task. Frontiers in Psychology, 2.

Conference proceedings

• McDonald TM, Ross M, Smith MT & Álvarez MA (2023) Nonparametric gaussian process covariances via multidimensional convolutions. Proceedings of Machine Learning Research, Vol. 206 (pp 8279-8293). Palau de Congressos, Valencia, Spain, 25 April 2023 - 25 April 2023. View this article in WRRO
• Gahungu P, Lanyon CW, Álvarez MA, Bainomugisha E, Smith MT & Wilkinson RD (2022) Adjoint-aided inference of Gaussian process driven differential equations. Advances in Neural Information Processing Systems (NeurIPS 2022), Vol. 35. New Orleans, LA, USA, 28 November 2022 - 28 November 2022. View this article in WRRO
• Grosse K, Smith MT & Backes M (2021) Killing four birds with one Gaussian Process: The relation between different test-time attacks. 2020 25th International Conference on Pattern Recognition (ICPR) Proceedings (pp 4696-4703). MIlan, Italy, 10 January 2021 - 10 January 2021. View this article in WRRO
• Yousefi F, Smith MT & Alvarez MA (2019) Multi-task Learning for aggregated data using Gaussian processes. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), Vol. 32 (pp 15050-15060). Vancouver, Canada, 8 December 2019 - 8 December 2019. View this article in WRRO
• Yousefi F, Smith MT & Alvarez Lopez M (2019) Multi-task Learning for aggregated data using Gaussian processes. Proceedings of the conference on Advances in Neural Information Processing Systems (NIPS 2019), Vol. 32. Vancouver, Canada, 8 December 2019 - 8 December 2019. View this article in WRRO
• Smith MT, Alvarez MA, Zwiessele M & Lawrence ND () Differentially private regression with Gaussian processes. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics(84) (pp 1195-1203). Lanzarote, Canary Islands, 9 April 2018 - 9 April 2018. View this article in WRRO

Preprints

• Ross M, Smith MT & Álvarez MA (2021) Learning Nonparametric Volterra Kernels with Gaussian Processes, arXiv.
• Smith M (2019) The Limitations of Model Uncertainty in Adversarial Settings.
• Smith MT, Alvarez MA & Lawrence ND (2019) Differentially Private Regression and Classification with Sparse Gaussian Processes, arXiv.
• Yousefi F, Smith MT & Álvarez MA (2019) Multi-task Learning for Aggregated Data using Gaussian Processes, arXiv.
• Smith MT, Alvarez MA & Lawrence ND (2018) Gaussian Process Regression for Binned Data, arXiv.