Amos Storkey - Google Scholar Citations

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	All	Since 2015
Citations	13265	9424
h-index	35	28
i10-index	71	51

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Co-authors

Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Harrison EdwardsOpenAIVerified email at openai.com
Jonathan D. ClaydenLecturer in Neuroimaging and Biophysics, UCL GOS Institute of Child Health, University CollegeVerified email at ucl.ac.uk
Krzysztof J. GorgolewskiGoogle LLCVerified email at google.com
Cyril PernetSenior Academic Fellow, University of EdinburghVerified email at ed.ac.uk
Marc ToussaintProfessor of Computer Science, University of Stuttgart, GermanyVerified email at informatik.uni-stuttgart.de
Antreas AntoniouUniversity of EdinburghVerified email at sms.ed.ac.uk
Yoshua BengioProfessor, University of Montreal (Computer Sc. & Op. Res.), Mila, CIFAR, CRM, IVADO, REPARTI, GRSNCVerified email at mila.quebec
Susana Muñoz ManiegaResearch Fellow, University of EdinburghVerified email at ed.ac.uk
David P. ReichertGoogle DeepMindVerified email at google.com
Romain ValabregueCENIR ICMVerified email at upmc.fr
Peggy SerièsSenior Lecturer in Informatics, University EdinburghVerified email at inf.ed.ac.uk
S LawrieProfessor of Psychiatry, University of EdinburghVerified email at ed.ac.uk
Lawrence MurrayUber AIVerified email at uber.com
Andrew DaiGoogle BrainVerified email at google.com
Stefan HarmelingProfessor at Heinrich-Heine-Universität DüsseldorfVerified email at hhu.de
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Krzysztof J. GerasNew York UniversityVerified email at nyu.edu
Jonathan MillinUniversity of EdinburghVerified email at sms.ed.ac.uk

Amos Storkey

Professor of Machine Learning and AI, School of Informatics, University of Edinburgh, UK

Verified email at ed.ac.uk

Deep Learning Machine Learning Bayesian Methods Prediction Markets diffusion MRI


Title	Cited by	Year
The pascal visual object classes (voc) challenge M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman International journal of computer vision 88 (2), 303-338, 2010	9461*	2010
The 2005 pascal visual object classes challenge M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ... Machine Learning Challenges Workshop, 117-176, 2005	267	2005
Data augmentation generative adversarial networks A Antoniou, A Storkey, H Edwards arXiv preprint arXiv:1711.04340, 2017	195	2017
Probabilistic inference for solving discrete and continuous state Markov Decision Processes M Toussaint, A Storkey Proceedings of the 23rd international conference on Machine learning, 945-952, 2006	167	2006
Training deep convolutional neural networks to play go C Clark, A Storkey arXiv:1412.3409, 2014, and Proceedings of the 32nd International Conference …, 2014	158	2014
Towards a neural statistician H Edwards, A Storkey arXiv preprint arXiv:1606.02185, 2016	156	2016
Censoring Representations with an Adversary H Edwards, A Storkey Proceedings of ICLR and arXiv preprint arXiv:1511.05897, 2015	156	2015
When training and test sets are different: characterizing learning transfer A Storkey Dataset shift in machine learning, 3-28, 2009	125	2009
Large-scale study of curiosity-driven learning Y Burda, H Edwards, D Pathak, A Storkey, T Darrell, AA Efros arXiv preprint arXiv:1808.04355, 2018	121	2018
Test–retest reliability of structural brain networks from diffusion MRI CR Buchanan, CR Pernet, KJ Gorgolewski, AJ Storkey, ME Bastin Neuroimage 86, 231-243, 2014	104	2014
Exploration by random network distillation Y Burda, H Edwards, A Storkey, O Klimov arXiv preprint arXiv:1810.12894, 2018	101	2018
The basins of attraction of a new Hopfield learning rule AJ Storkey, R Valabregue Neural Networks 12 (6), 869-876, 1999	95	1999
Three factors influencing minima in sgd S Jastrzębski, Z Kenton, D Arpit, N Ballas, A Fischer, Y Bengio, A Storkey arXiv preprint arXiv:1711.04623, 2017	93	2017
Probabilistic inference for solving (PO)MDPs M Toussaint, S Harmeling, A Storkey School of Informatics Technical Report, 2006	91	2006
TractoR: magnetic resonance imaging and tractography with R JD Clayden, SM Maniega, AJ Storkey, MD King, ME Bastin, CA Clark Journal of Statistical Software 44 (8), 1-18, 2011	83	2011
Mixture regression for covariate shift AJ Storkey, M Sugiyama Advances in Neural Information Processing Systems, 1337-1344, 2006	80*	2006
A probabilistic model-based approach to consistent white matter tract segmentation JD Clayden, AJ Storkey, ME Bastin IEEE transactions on medical imaging 26 (11), 1555-1561, 2007	77	2007
Single subject fMRI test–retest reliability metrics and confounding factors KJ Gorgolewski, AJ Storkey, ME Bastin, I Whittle, C Pernet Neuroimage 69, 231-243, 2013	71	2013
Improved segmentation reproducibility in group tractography using a quantitative tract similarity measure JD Clayden, ME Bastin, AJ Storkey NeuroImage 33 (2), 482-492, 2006	59	2006
Increasing the capacity of a Hopfield network without sacrificing functionality A Storkey International Conference on Artificial Neural Networks, 451-456, 1997	58	1997

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