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Michael Smith
Michael Smith
Computer Science, University of Sheffield
Verified email at sheffield.ac.uk - Homepage
Title
Cited by
Cited by
Year
Differentially private regression with Gaussian processes
MT Smith, MA Álvarez, M Zwiessele, ND Lawrence
International Conference on Artificial Intelligence and Statistics, 1195-1203, 2018
59*2018
The limitations of model uncertainty in adversarial settings
K Grosse, D Pfaff, MT Smith, M Backes
arXiv preprint arXiv:1812.02606, 2018
462018
The postsubiculum and spatial learning: the role of postsubicular synaptic activity and synaptic plasticity in hippocampal place cell, object, and object-location memory
D Bett, CH Stevenson, KL Shires, MT Smith, SJ Martin, PA Dudchenko, ...
Journal of Neuroscience 33 (16), 6928-6943, 2013
352013
Multi-task learning for aggregated data using Gaussian processes
F Yousefi, MT Smith, M Alvarez
Advances in Neural Information Processing Systems 32, 2019
342019
Physiological signal variability in hMT+ reflects performance on a direction discrimination task
MG Wutte, MT Smith, VL Flanagin, T Wolbers
Frontiers in psychology 2, 9664, 2011
272011
Hospitalization and mortality following non-attendance for hemodialysis according to dialysis day of the week: a European cohort study
J Fotheringham, MT Smith, M Froissart, F Kronenberg, P Stenvinkel, ...
BMC nephrology 21, 1-10, 2020
132020
Gaussian process regression for binned data
MT Smith, MA Alvarez, ND Lawrence
arXiv preprint arXiv:1809.02010, 2018
12*2018
A method for low‐cost, low‐impact insect tracking using retroreflective tags
MT Smith, M Livingstone, R Comont
Methods in Ecology and Evolution 12 (11), 2184-2195, 2021
112021
Killing four birds with one Gaussian process: The relation between different test-time attacks
K Grosse, MT Smith, M Backes
2020 25th International Conference on Pattern Recognition (ICPR), 4696-4703, 2021
11*2021
Adversarial vulnerability bounds for Gaussian process classification
MT Smith, K Grosse, M Backes, MA Alvarez
Machine Learning 112 (3), 971-1009, 2023
102023
Learning nonparametric Volterra kernels with Gaussian processes
M Ross, MT Smith, M Álvarez
Advances in neural information processing systems 34, 24099-24110, 2021
92021
How wrong am I?-Studying adversarial examples and their impact on uncertainty in Gaussian process machine learning models
K Grosse, D Pfaff, MT Smith, M Backes
arXiv preprint arXiv:1711.06598, 2017
82017
Adjoint-aided inference of Gaussian process driven differential equations
P Gahungu, C Lanyon, MA Álvarez, E Bainomugisha, MT Smith, ...
Advances in Neural Information Processing Systems 35, 17233-17247, 2022
52022
Malaria surveillance with multiple data sources using Gaussian process models
M Mubangizi, R Andrade-Pacheco, M Smith, JA Quinn, N Lawrence
1st International Conference on the Use of Mobile ICT in Africa, 2014
42014
Fluctuations in the open time of synaptic channels: an application to noise analysis based on charge
H Feldwisch-Drentrup, AB Barrett, MT Smith, MCW van Rossum
Journal of neuroscience methods 210 (1), 15-21, 2012
42012
Differentially private regression and classification with sparse Gaussian processes
MT Smith, MA Álvarez, ND Lawrence
Journal of Machine Learning Research 22 (188), 1-41, 2021
32021
Shallow and Deep Nonparametric Convolutions for Gaussian Processes
TM McDonald, M Ross, MT Smith, MA Álvarez
arXiv preprint arXiv:2206.08972, 2022
22022
Machine Learning for a Low-cost Air Pollution Network
MT Smith, J Ssematimba, MA Álvarez, E Bainomugisha
arXiv preprint arXiv:1911.12868, 2019
22019
Modelling calibration uncertainty in networks of environmental sensors
MT Smith, M Ross, J Ssematimba, MA Álvarez, E Bainomugisha, ...
Journal of the Royal Statistical Society Series C: Applied Statistics 72 (5 …, 2023
12023
Nonparametric Gaussian Process Covariances via Multidimensional Convolutions
TM McDonald, M Ross, MT Smith, MA Álvarez
International Conference on Artificial Intelligence and Statistics, 8279-8293, 2023
12023
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