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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
39942015
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
23392018
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
8682019
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
2412020
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
S Filippi, C Barnes, J Cornebise, MPH Stumpf
1572011
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
1082020
Deep learning and data labeling for medical applications
G Carneiro, D Mateus, L Peter, A Bradley, JMRS Tavares, V Belagiannis, ...
1002016
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
992008
Proceedings of the 32nd International Conference on Machine Learning
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra, F Bach, D Blei
PMLR 37, 1613-1622, 2015
902015
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
692021
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
622016
Open high-resolution satellite imagery: The worldstrat dataset–with application to super-resolution
J Cornebise, I Oršolić, F Kalaitzis
Advances in Neural Information Processing Systems 35, 25979-25991, 2022
392022
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
362019
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, 2016
282016
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
252013
Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with …
G Carneiro, D Mateus, L Peter, A Bradley, JMRS Tavares, V Belagiannis, ...
Springer, 2016
172016
Adaptive sequential Monte Carlo by means of mixture of experts
J Cornebise, E Moulines, J Olsson
Statistics and Computing 24, 317-337, 2014
172014
Opportunities and risks of LLMs for scalable deliberation with Polis
CT Small, I Vendrov, E Durmus, H Homaei, E Barry, J Cornebise, ...
arXiv preprint arXiv:2306.11932, 2023
142023
Adaptive Sequential Monte Carlo Methods
J Cornebise
University Pierre of Marie Curie, Paris, 45-76, 2009
142009
Signal processing systems
JRM Cornebise, DJ Rezende, DP Wierstra
US Patent 9,342,781, 2016
132016
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Articles 1–20