George Deligiannidis

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	All	Since 2016
Citations	610	507
h-index	10	10
i10-index	11	10

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Co-authors

Arnaud DoucetProfessor of Statistics, University of Oxford & Research Scientist, Google DeepMindVerified email at stats.ox.ac.uk
M PittKing's College LondonVerified email at kcl.ac.uk
robert kohnProfessor of Economics University of New South WalesVerified email at unsw.edu.au
Rob CornishUniversity of OxfordVerified email at robots.ox.ac.uk
Pierre E. JacobAssociate Professor, Department of Statistics, Harvard UniversityVerified email at fas.harvard.edu
Lawrence MiddletonAstraZenecaVerified email at astrazeneca.com
Adrian N. BishopUTS; CSIRO; ANUVerified email at anu.edu.au
Jeremy HengAssistant Professor of Statistics, ESSEC Business SchoolVerified email at essec.edu
Anthony CateriniDPhil Student in Statistics, University of OxfordVerified email at st-hughs.ox.ac.uk
Sebastian SchmonComplexity Research, ImprobableVerified email at stats.ox.ac.uk
Zemer KosloffHebrew University of JerusalemVerified email at mail.huji.ac.il
Daniel PaulinLecturer of Statistics and Data Science, University of EdinburghVerified email at ed.ac.uk
Saifuddin SyedUniversity of British ColumbiaVerified email at stat.ubc.ca
Anthony LeeSchool of Mathematics, University of BristolVerified email at bristol.ac.uk
Edina RostaUniversity College LondonVerified email at ucl.ac.uk
Fahim FaiziKing's College LondonVerified email at kcl.ac.uk
Umut SimsekliINRIA - École Normale SupérieureVerified email at inria.fr
Ozan SenerIntel LabsVerified email at cs.stanford.edu
Murat A. ErdogduStanford UniversityVerified email at stanford.edu
Magda PeligradTaft Professor University of CincinnatiVerified email at ucmail.uc.edu

George Deligiannidis

Associate Professor in Statistics, University of Oxford

Verified email at stats.ox.ac.uk - Homepage

Monte-Carlo probability learning theory machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator A Doucet, MK Pitt, G Deligiannidis, R Kohn Biometrika 102 (2), 295-313, 2015	251	2015
The Correlated Pseudo-Marginal Method G Deligiannidis, A Doucet, MK Pitt JRSSB 80 (5), 839–870, 2015	92	2015
Piecewise-Deterministic Markov Chain Monte Carlo P Vanetti, A Bouchard-Côté, G Deligiannidis, A Doucet arXiv preprint arXiv:1707.05296, 2017	56	2017
Controlled sequential monte carlo J Heng, AN Bishop, G Deligiannidis, A Doucet Annals of Statistics 48 (5), 2904 - 2929, 2017	36	2017
Exponential Ergodicity of the Bouncy Particle Sampler G Deligiannidis, A Bouchard-Côté, A Doucet Annals of Statistics 47 (3), 1268-1287, 2019	26	2019
Asymptotic variance of the self-intersections of stable random walks using Darboux-Wiener theory G Deligiannidis, SA Utev Siberian mathematical journal 52 (4), 639-650, 2011	22	2011
Optimal Stopping for processes with independent increments, and applications G Deligiannidis, H Le, S Utev Journal of Applied Probability 46 (4), 1130-1145, 2009	19	2009
Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates G Deligiannidis, D Paulin, A Bouchard-Côté, A Doucet Accepted at Annals of Applied Probability, 2018	16	2018
Unbiased Markov chain Monte Carlo for intractable target distributions L Middleton, G Deligiannidis, A Doucet, PE Jacob arXiv preprint arXiv:1807.08691, 2018	12	2018
Non-reversible parallel tempering: a scalable highly parallel MCMC scheme S Syed, A Bouchard-Côté, G Deligiannidis, A Doucet arXiv preprint arXiv:1905.02939, 2019	10	2019
Unbiased smoothing using particle independent Metropolis-Hastings L Middleton, G Deligiannidis, A Doucet, PE Jacob The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	10	2019
Scalable Metropolis-Hastings for exact Bayesian inference with large datasets R Cornish, P Vanetti, A Bouchard-Côté, G Deligiannidis, A Doucet ICML, 2019	9	2019
Which ergodic averages have finite asymptotic variance? G Deligiannidis, A Lee Annals of Applied Probability 28 (4), 2309-2334, 2018	9	2018
Large sample asymptotics of the pseudo-marginal method SM Schmon, G Deligiannidis, A Doucet, MK Pitt to appear in Biometrika, arXiv preprint arXiv:1806.10060, 2018	8	2018
Relaxing bijectivity constraints with continuously indexed normalising flows R Cornish, A Caterini, G Deligiannidis, A Doucet International Conference on Machine Learning, 2133-2143, 2020	7	2020
Localised generative flows R Cornish, A Caterini, G Deligiannidis, A Doucet	4	2019
Relative Complexity of Random Walks in Random Scenery in the absence of a weak invariance principle for the local times G Deligiannidis, Z Kosloff Annals of Probability 45 (4), 2505-2532, 2017	4	2017
An asymptotic variance of the self-intersections of random walks G Deligiannidis, S Utev arXiv preprint arXiv:1004.4845, 2010	4	2010
Bernoulli race particle filters SM Schmon, A Doucet, G Deligiannidis The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	3	2019
Boundary of the Range of a random walk and the F\" olner property G Deligiannidis, S Gouëzel, Z Kosloff arXiv preprint arXiv:1810.10454, 2018	3	2018

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