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Julien Cornebise
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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
22242015
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
14192018
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
4892019
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
S Filippi, C Barnes, J Cornebise, MPH Stumpf
1222011
Adaptive methods for sequential importance sampling with application to state space models
J Cornebise, É Moulines, J Olsson
Statistics and Computing 18 (4), 461-480, 2008
932008
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), 1-6, 2020
612020
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, 2016
512016
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
342020
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
272013
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
252016
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
192019
Adaptative sequential Monte Carlo methods
J Cornebise
172009
Adaptive sequential Monte Carlo by means of mixture of experts
J Cornebise, E Moulines, J Olsson
Statistics and Computing 24 (3), 317-337, 2014
152014
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
112021
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
72011
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
62018
Highres-net: Multi-frame super-resolution by recursive fusion
M Deudon, A Kalaitzis, MR Arefin, I Goytom, Z Lin, K Sankaran, ...
52019
A Meteosat Second Generation receiving, processing and storing images system developed by engineer students
L Beaudoin, LA Charbardes, J Cornebise, C Dufour, K Florczak, F Gachot, ...
Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium …, 2005
52005
Recommending content using neural networks
C Blundell, JRM Cornebise
US Patent 10,438,114, 2019
42019
Signal processing systems
JRM Cornebise, DJ Rezende, DP Wierstra
US Patent 9,342,781, 2016
32016
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