Amos Storkey - Google Scholar

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	All	Since 2015
Citations	4771	3369
h-index	37	31
i10-index	77	58

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Co-authors

Harrison EdwardsOpenAIVerified email at openai.com
Antreas AntoniouUniversity of EdinburghVerified email at sms.ed.ac.uk
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, TU Berlin, GermanyVerified email at informatik.uni-stuttgart.de
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
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
Andrew DaiGoogle BrainVerified email at google.com
Lawrence MurrayUber AIVerified email at uber.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
Alan BundyProfessor of Automated Reasoning, University of EdinburghVerified email at ed.ac.uk
Krzysztof J. GerasNew York UniversityVerified email at nyu.edu

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


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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	374	2005
Data augmentation generative adversarial networks A Antoniou, A Storkey, H Edwards arXiv preprint arXiv:1711.04340, 2017	298	2017
Exploration by random network distillation Y Burda, H Edwards, A Storkey, O Klimov arXiv preprint arXiv:1810.12894, 2018	215	2018
Censoring Representations with an Adversary H Edwards, A Storkey Proceedings of ICLR and arXiv preprint arXiv:1511.05897, 2015	207	2015
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	197	2018
Towards a neural statistician H Edwards, A Storkey arXiv preprint arXiv:1606.02185, 2016	196	2016
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	181	2006
When training and test sets are different: characterizing learning transfer A Storkey Dataset shift in machine learning, 3-28, 2009	159	2009
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	138	2017
Training deep convolutional neural networks to play go C Clark, A Storkey arXiv:1412.3409, 2014, and Proceedings of the 32nd International Conference …, 2014	124	2014
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	118	2014
The basins of attraction of a new Hopfield learning rule AJ Storkey, R Valabregue Neural Networks 12 (6), 869-876, 1999	100	1999
How to train your MAML A Antoniou, H Edwards, A Storkey arXiv preprint arXiv:1810.09502, 2018	96	2018
Probabilistic inference for solving (PO)MDPs M Toussaint, S Harmeling, A Storkey School of Informatics Technical Report, 2006	92	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	89	2011
Mixture regression for covariate shift AJ Storkey, M Sugiyama Advances in Neural Information Processing Systems, 1337-1344, 2006	89*	2006
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	81	2013
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
Increasing the capacity of a Hopfield network without sacrificing functionality A Storkey International Conference on Artificial Neural Networks, 451-456, 1997	62	1997
Modelling motion primitives and their timing in biologically executed movements B Williams, M Toussaint, AJ Storkey Advances in neural information processing systems, 1609-1616, 2008	59	2008

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