Alexandre Thiery

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Michaël J.A. GirardAssociate Professor, Duke-NUS Medical School; Principal Investigator, SERIVerified email at ophthalmic.engineering
Chris SherlockLancaster UniversityVerified email at lancaster.ac.uk
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Andrew M StuartComputing + Mathematical Sciences, CaltechVerified email at caltech.edu
Ajay JasraProfessor of Data Science, CUHK, SZVerified email at cuhk.edu.cn
Alexandros BeskosProfessor in Statistics, UCLVerified email at ucl.ac.uk
Gareth RobertsProfessor of Statistics, University of WarwickVerified email at warwick.ac.uk
Matthew M. GrahamResearch data scientist, University College LondonVerified email at ucl.ac.uk
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Jeffrey S. RosenthalProfessor of Statistics, University of TorontoVerified email at math.toronto.edu
Nikolas KantasDept. of Mathematics, Imperial College LondonVerified email at imperial.ac.uk
Axel FinkeDepartment of Mathematics, Loughborough University, UKVerified email at lboro.ac.uk
Touati BenoukrafAssociate Professor, Memorial University of Newfoundland | Faculty of MedicineVerified email at mun.ca
Pierre E. JacobESSEC Business SchoolVerified email at essec.edu
Deborshee SenSr Data Scientist, GoogleVerified email at google.com
Anthony LeeSchool of Mathematics, University of BristolVerified email at bristol.ac.uk
Daniel PaulinLecturer of Statistics and Data Science, University of EdinburghVerified email at ed.ac.uk
Andrew GolightlyDurham University, UKVerified email at durham.ac.uk
Thibault VogtAssociate ProfessorVerified email at mail.sysu.edu.cn
Chao WangUniversity of Kansas Medical CenterVerified email at kumc.edu

Alexandre Thiery

Associate Professor, National University of Singapore (NUS)

Verified email at nus.edu.sg - Homepage

Monte Carlo methods Machine Leaning Deep Learning


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Consistency and fluctuations for stochastic gradient Langevin dynamics Y Whye Teh, A Thiéry, S Vollmer Journal of Machine Learning Research 17 (7), 1−33, 2016	256	2016
On the efficiency of pseudo-marginal random walk Metropolis algorithms C Sherlock, AH Thiery, GO Roberts, JS Rosenthal	216	2015
DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images SK Devalla, PK Renukanand, BK Sreedhar, G Subramanian, L Zhang, ... Biomedical optics express 9 (7), 3244-3265, 2018	193	2018
Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore PN Pratanwanich, F Yao, Y Chen, CWQ Koh, YK Wan, C Hendra, P Poon, ... Nature biotechnology 39 (11), 1394-1402, 2021	154	2021
Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions NS Pillai, AM Stuart, AH Thiéry	120	2012
Uncertainty quantification and deep ensembles R Rahaman, AH Thiery Advances in Neural Information Processing Systems 34, 2021	113	2021
On the convergence of adaptive sequential Monte Carlo methods A Beskos, A Jasra, N Kantas, A Thiery Annals of Applied Probability 26 (2), 1111-1146, 2016	109	2016
A deep learning approach to digitally stain optical coherence tomography images of the optic nerve head SK Devalla, KS Chin, JM Mari, TA Tun, NG Strouthidis, T Aung, AH Thiéry, ... Investigative ophthalmology & visual science 59 (1), 63-74, 2018	107	2018
A deep learning approach to denoise optical coherence tomography images of the optic nerve head SK Devalla, G Subramanian, TH Pham, X Wang, S Perera, TA Tun, ... Scientific reports 9 (1), 14454, 2019	101	2019
NanoVar: accurate characterization of patients’ genomic structural variants using low-depth nanopore sequencing CY Tham, R Tirado-Magallanes, Y Goh, MJ Fullwood, BTH Koh, W Wang, ... Genome biology 21, 1-15, 2020	93	2020
Glaucoma management in the era of artificial intelligence SK Devalla, Z Liang, TH Pham, C Boote, NG Strouthidis, AH Thiery, ... British Journal of Ophthalmology 104 (3), 301-311, 2020	84	2020
On non-negative unbiased estimators PE Jacob, AH Thiery The Annals of Statistics 43 (2), 769--784, 2015	84	2015
Detection of m6A from direct RNA sequencing using a multiple instance learning framework C Hendra, PN Pratanwanich, YK Wan, WSS Goh, A Thiery, J Göke Nature methods 19 (12), 1590-1598, 2022	77	2022
Probabilistic forecasting of day-ahead solar irradiance using quantile gradient boosting H Verbois, A Rusydi, A Thiery Solar Energy 173, 313-327, 2018	67	2018
A systematic benchmark of Nanopore long read RNA sequencing for transcript level analysis in human cell lines Y Chen, NM Davidson, YK Wan, H Patel, F Yao, HM Low, C Hendra, ... BioRxiv, 2021.04. 21.440736, 2021	59	2021
Pseudo-marginal Metropolis–Hastings sampling using averages of unbiased estimators C Sherlock, AH Thiery, A Lee Biometrika 104 (3), 727-734, 2017	34	2017
Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images TH Pham, SK Devalla, A Ang, ZD Soh, AH Thiery, C Boote, CY Cheng, ... British Journal of Ophthalmology 105 (9), 1231-1237, 2021	33	2021
Towards label-free 3D segmentation of optical coherence tomography images of the optic nerve head using deep learning SK Devalla, TH Pham, SK Panda, L Zhang, G Subramanian, ... Biomedical optics express 11 (11), 6356-6378, 2020	31	2020
DeshadowGAN: a deep learning approach to remove shadows from optical coherence tomography images H Cheong, SK Devalla, TH Pham, L Zhang, TA Tun, X Wang, S Perera, ... Translational Vision Science & Technology 9 (2), 23-23, 2020	31	2020
Noisy gradient flow from a random walk in Hilbert space NS Pillai, AM Stuart, AH Thiéry Stochastic Partial Differential Equations: Analysis and Computations 2, 196-232, 2014	29*	2014

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