Folgen
Edward Wagstaff
Edward Wagstaff
Machine Learning Scientist, Prescient Design
Bestätigte E-Mail-Adresse bei robots.ox.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
On the limitations of representing functions on sets
E Wagstaff, FB Fuchs, M Engelcke, I Posner, M Osborne
ICML 2019, 2019
2282019
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
752022
Iterative SE (3)-Transformers
FB Fuchs, E Wagstaff, J Dauparas, I Posner
Geometric Science of Information 5, 585-595, 2021
242021
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
152019
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
Batch selection for parallelisation of Bayesian quadrature
E Wagstaff, S Hamid, M Osborne
arXiv preprint arXiv:1812.01553, 2018
32018
VBALD-Variational Bayesian approximation of log determinants
D Granziol, E Wagstaff, BX Ru, M Osborne, S Roberts
arXiv preprint arXiv:1802.08054, 2018
32018
Lab-in-the-loop therapeutic antibody design with deep learning
NC Frey, I Hotzel, SD Stanton, RL Kelly, RG Alberstein, EK Makowski, ...
bioRxiv, 2025.02. 19.639050, 2025
2025
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
Generalizing to any diverse distribution: uniformity & rebalancing
A Loukas, K Martinkus, E Wagstaff, K Cho
Workshop on Spurious Correlation and Shortcut Learning: Foundations and …, 0
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–11