Julien Cornebise
Title
Cited by
Cited by
Year
Weight uncertainty in neural networks
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra
arXiv preprint arXiv:1505.05424, 2015
10492015
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
6772018
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
1802019
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
S Filippi, C Barnes, J Cornebise, MPH Stumpf
932011
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
852008
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
352016
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
112014
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
102019
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
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
32020
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
32018
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
Buffers for electrophoresis and use thereof
KJ Hacker, KO Voss
US Patent 7,282,128, 2007
32007
Adaptive refueling in particle filter algorithms
J Cornebise, E Moulines, J Olsson
Workshop New directions in Monte Carlo Methods, Fleurance, 25-29, 2007
32007
A practical implementation of the Gibbs sampler for mixture of distributions: Application to the determination of specifications in food industry
J Cornebise, M Maumy, P Girard
32005
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Articles 1–20