On the limitations of representing functions on sets E Wagstaff, FB Fuchs, M Engelcke, I Posner, M Osborne ICML 2019, 2019 | 219 | 2019 |
Universal approximation of functions on sets E Wagstaff, FB Fuchs, M Engelcke, MA Osborne, I Posner Journal of Machine Learning Research 23 (151), 1-56, 2022 | 59 | 2022 |
Iterative SE (3)-Transformers FB Fuchs, E Wagstaff, J Dauparas, I Posner Geometric Science of Information 5, 585-595, 2021 | 21 | 2021 |
Prediction of GNSS phase scintillations: A machine learning approach K Lamb, G Malhotra, A Vlontzos, E Wagstaff, AG Baydin, A Bhiwandiwalla, ... arXiv preprint arXiv:1910.01570, 2019 | 13 | 2019 |
Correlation of auroral dynamics and GNSS scintillation with an autoencoder K Lamb, G Malhotra, A Vlontzos, E Wagstaff, AG Baydin, A Bhiwandiwalla, ... arXiv preprint arXiv:1910.03085, 2019 | 4 | 2019 |
Batch selection for parallelisation of Bayesian quadrature E Wagstaff, S Hamid, M Osborne arXiv preprint arXiv:1812.01553, 2018 | 3 | 2018 |
VBALD-Variational Bayesian approximation of log determinants D Granziol, E Wagstaff, BX Ru, M Osborne, S Roberts arXiv preprint arXiv:1802.08054, 2018 | 3 | 2018 |
Exploiting prior knowledge in machine learning model design E Wagstaff University of Oxford, 2021 | | 2021 |
A deep-learning based approach for predicting high latitude ionospheric scintillations using geospace data and auroral imagery G Malhotra, A Vlontzos, K Lamb, E Wagstaff, A Bhatt AGU Fall Meeting Abstracts 2019, NG21A-08, 2019 | | 2019 |