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Julien Cornebise
Julien Cornebise
Hon. Associate Professor, University College London
Dirección de correo verificada de ucl.ac.uk - Página principal
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Weight uncertainty in neural network
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra
International conference on machine learning, 1613-1622, 2015
29042015
Clinically applicable deep learning for diagnosis and referral in retinal disease
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
Nature medicine 24 (9), 1342-1350, 2018
17902018
A clinically applicable approach to continuous prediction of future acute kidney injury
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
Nature 572 (7767), 116-119, 2019
6322019
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
S Filippi, C Barnes, J Cornebise, MPH Stumpf
1402011
AI for social good: unlocking the opportunity for positive impact
N Tomašev, J Cornebise, F Hutter, S Mohamed, A Picciariello, B Connelly, ...
Nature Communications 11 (1), 2468, 2020
1192020
Adaptive methods for sequential importance sampling with application to state space models
J Cornebise, É Moulines, J Olsson
Statistics and Computing 18, 461-480, 2008
962008
Highres-net: Recursive fusion for multi-frame super-resolution of satellite imagery
M Deudon, A Kalaitzis, I Goytom, MR Arefin, Z Lin, K Sankaran, ...
arXiv preprint arXiv:2002.06460, 2020
662020
Automated analysis of retinal imaging using machine learning techniques for computer vision
J De Fauw, P Keane, N Tomasev, D Visentin, G van den Driessche, ...
F1000Research 5 (1573), 1573, 2016
572016
Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
N Tomašev, N Harris, S Baur, A Mottram, X Glorot, JW Rae, M Zielinski, ...
Nature Protocols 16 (6), 2765-2787, 2021
302021
D., Wierstra. Weight uncertainty in neural network
C Blundell, J Cornebise, K Kavukcuoglu
Proceedings, of the 32nd International Conference on Machine Learning,(ICML …, 2015
292015
Adaptive Markov chain Monte Carlo forward projection for statistical analysis in epidemic modelling of human papillomavirus
IA Korostil, GW Peters, J Cornebise, DG Regan
Statistics in medicine 32 (11), 1917-1953, 2013
292013
Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans
C Chu, J De Fauw, N Tomasev, BR Paredes, C Hughes, J Ledsam, ...
F1000Research 5 (2104), 2104, 2016
262016
A large-scale crowdsourced analysis of abuse against women journalists and politicians on Twitter
L Delisle, A Kalaitzis, K Majewski, A de Berker, M Marin, J Cornebise
arXiv preprint arXiv:1902.03093, 2019
232019
Adaptive Sequential Monte Carlo Methods
J Cornebise
University Pierre of Marie Curie, Paris, 45-76, 2009
162009
Adaptive sequential Monte Carlo by means of mixture of experts
J Cornebise, E Moulines, J Olsson
Statistics and Computing 24, 317-337, 2014
152014
Highres-net: Multi-frame super-resolution by recursive fusion
M Deudon, A Kalaitzis, MR Arefin, I Goytom, Z Lin, K Sankaran, ...
82020
A comparative study of Monte-Carlo methods for multitarget tracking
F Septier, J Cornebise, S Godsill, Y Delignon
2011 IEEE Statistical Signal Processing Workshop (SSP), 205-208, 2011
82011
Witnessing atrocities: quantifying villages destruction in Darfur with crowdsourcing and transfer learning
J Cornebise, D Worrall, M Farfour, M Marin
Proc. AI for Social Good NeurIPS2018 Workshop, NeurIPS’18, 2018
72018
Recommending content using neural networks
C Blundell, JRM Cornebise
US Patent 10,438,114, 2019
62019
A meteosat second generation receiving, processing and storing images system developed by engineer students.
L Beaudoin, LA Charbardès, J Cornebise, C Dufour, K Florczak, F Gachot, ...
IGARSS, 3159-3162, 2005
52005
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Artículos 1–20