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Edward Wagstaff
Edward Wagstaff
Machine Learning Scientist, Prescient Design
Verified email at robots.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
On the limitations of representing functions on sets
E Wagstaff, FB Fuchs, M Engelcke, I Posner, M Osborne
ICML 2019, 2019
1542019
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
162022
Iterative SE (3)-Transformers
FB Fuchs, E Wagstaff, J Dauparas, I Posner
Geometric Science of Information 5, 585-595, 2021
122021
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
112019
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
42019
VBALD-Variational Bayesian approximation of log determinants
D Granziol, E Wagstaff, BX Ru, M Osborne, S Roberts
arXiv preprint arXiv:1802.08054, 2018
32018
Batch Selection for Parallelisation of Bayesian Quadrature
E Wagstaff, S Hamid, M Osborne
arXiv preprint arXiv:1812.01553, 2018
22018
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
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