Oliver Johnson

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Matthew AldridgeUniversity of LeedsVerified email at leeds.ac.uk
Ioannis KontoyiannisUniversity of CambridgeVerified email at cam.ac.uk
Robert PiechockiUniversity of BristolVerified email at bristol.ac.uk
Jonathan ScarlettAssistant Professor, Computer Science and Mathematics, National University of SingaporeVerified email at comp.nus.edu.sg
Mokshay MadimanUniversity of DelawareVerified email at udel.edu
Peter HarremoesLektor i matematik, Niels BrockVerified email at niels.brock.dk
Dino SejdinovicProfessor, University of AdelaideVerified email at adelaide.edu.au
Andrew R BarronProfessor of Statistics, Yale UniversityVerified email at yale.edu
Michael PocockNERC Centre for Ecology & HydrologyVerified email at ceh.ac.uk
Andrea TassiChief Engineer (5G/6G Research - AI & Development) at Samsung R&D Institute UKVerified email at samsung.com
Bogdan WarinschiUniversity of Bristol and DfinityVerified email at cs.bris.ac.uk
Fraser DalyHeriot-Watt UniversityVerified email at hw.ac.uk
A D BarbourUniversitaet ZuerichVerified email at math.uzh.ch
Christina GoldschmidtProfessor of ProbabilityVerified email at stats.ox.ac.uk
Jennifer ChakravartyResearch Fellow, University of BristolVerified email at bristol.ac.uk
Professor Andrew J TatemWorldPop, University of Southampton, UKVerified email at soton.ac.uk
Alessandro SorichettaUniversity of MilanVerified email at unimi.it
Angela DoufexiProfessor, University of BristolVerified email at bristol.ac.uk
Chrysanthi PaschouUniversity of BristolVerified email at bristol.ac.uk
Saikat GuhaProfessor, Peyghambarian Endowed Chair, College of Optical Sciences, University of ArizonaVerified email at optics.arizona.edu

Oliver Johnson

Professor of Information Theory, School of Mathematics, University of Bristol, UK

Verified email at bristol.ac.uk - Homepage

Information theory entropy probability Central Limit Theorem group testing


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Information theory and the central limit theorem OT Johnson World Scientific, 2004	357	2004
Group testing: an information theory perspective M Aldridge, O Johnson, J Scarlett Foundations and Trends in Communications and Information Theory 15 (3-4 …, 2019	224	2019
Fisher information inequalities and the central limit theorem O Johnson, A Barron Probability Theory and Related Fields 129, 391-409, 2004	162	2004
Group testing algorithms: Bounds and simulations M Aldridge, L Baldassini, O Johnson IEEE Transactions on Information Theory 60 (6), 3671-3687, 2014	155	2014
The capacity of adaptive group testing L Baldassini, O Johnson, M Aldridge 2013 IEEE International Symposium on Information Theory (ISIT), 2676-2680, 2013	97	2013
Some results concerning maximum Rényi entropy distributions O Johnson, C Vignat Annales de l'IHP Probabilités et statistiques 43 (3), 339-351, 2007	89	2007
Note on noisy group testing: Asymptotic bounds and belief propagation reconstruction D Sejdinovic, O Johnson 2010 48th Annual Allerton Conference on Communication, Control, and …, 2010	88	2010
Entropy and the law of small numbers I Kontoyiannis, P Harremoës, O Johnson IEEE Transactions on Information Theory 51 (2), 466-472, 2005	81	2005
Performance of Group Testing Algorithms With Near-Constant Tests Per Item O Johnson, M Aldridge, J Scarlett IEEE Transactions on Information Theory 65 (2), 707-723, 2019	71	2019
Log-concavity and the maximum entropy property of the Poisson distribution O Johnson Stochastic Processes and their Applications 117 (6), 791-802, 2007	71	2007
Central limit theorem and convergence to stable laws in Mallows distance O Johnson, R Samworth Bernoulli 11 (5), 829-845, 2005	61	2005
Encrypted Databases: New Volume Attacks against Range Queries Z Gui, O Johnson, B Warinschi Proceedings of the 26th ACM Conference on Computer and Communications …, 2019	54	2019
Log-concavity, ultra-log-concavity, and a maximum entropy property of discrete compound Poisson measures O Johnson, I Kontoyiannis, M Madiman Discrete Applied Mathematics 161 (9), 1232-1250, 2013	54*	2013
Compound Poisson approximation via information functionals AD Barbour, O Johnson, I Kontoyiannis, M Madiman Electronic Journal of Probability 15 (42), 1344-1368, 2010	41	2010
Preservation of log-concavity on summation O Johnson, C Goldschmidt ESAIM: Probability and Statistics 10, 206-215, 2006	41	2006
Thinning, entropy, and the law of thin numbers P Harremoës, O Johnson, I Kontoyiannis IEEE Transactions on Information Theory 56 (9), 4228-4244, 2010	37	2010
Monotonicity, thinning, and discrete versions of the entropy power inequality O Johnson, Y Yu IEEE Transactions on Information Theory 56 (11), 5387-5395, 2010	34	2010
Fisher information, compound Poisson approximation, and the Poisson channel M Madiman, O Johnson, I Kontoyiannis 2007 IEEE International Symposium on Information Theory (ISIT), 976-980, 2007	31	2007
Thinning and the law of small numbers P Harremoës, O Johnson, I Kontoyiannis 2007 IEEE International Symposium on Information Theory (ISIT), 1491-1495, 2007	31	2007
Reliability of broadcast communications under sparse random linear network coding S Brown, O Johnson, A Tassi IEEE Transactions on Vehicular Technology 67 (5), 4677-4682, 2018	30	2018

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