Julien Cornebise
Julien Cornebise
Hon. Associate Professor, University College London
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Weight uncertainty in neural networks
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra
arXiv preprint arXiv:1505.05424, 2015
12802015
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
8212018
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
2302019
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
S Filippi, C Barnes, J Cornebise, MPH Stumpf
972011
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
842008
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
382016
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
242013
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
202016
Adaptative sequential Monte Carlo methods
J Cornebise
162009
Adaptive sequential Monte Carlo by means of mixture of experts
J Cornebise, E Moulines, J Olsson
Statistics and Computing 24 (3), 317-337, 2014
132014
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
112019
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
72020
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
62011
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
62005
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
42020
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
42018
Recommending content using neural networks
C Blundell, JRM Cornebise
US Patent 10,438,114, 2019
32019
Signal processing systems
JRM Cornebise, DJ Rezende, DP Wierstra
US Patent 9,342,781, 2016
32016
Méthodes de Monte Carlo séquentielles adaptatives
J Cornebise
32009
Adaptive methods for sequential importance sampling
J Cornebise, E Moulines, J Olsson
Journ ées MAS de la SMAI, Rennes, France, 2008
32008
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Artículos 1–20