Amos Storkey

Cited by

	All	Since 2016
Citations	5590	3912
h-index	39	31
i10-index	79	57

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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
David P. ReichertGoogle DeepMindVerified email at google.com
Susana Muñoz ManiegaResearch Fellow, University of EdinburghVerified email at ed.ac.uk
Romain ValabregueCENIR ICMVerified email at upmc.fr
Peggy SerièsSenior Lecturer in Informatics, University EdinburghVerified email at inf.ed.ac.uk
Stephen 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 Distinguished Researcher, GoogleVerified 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
Simo SärkkäAssociate Professor, Aalto UniversityVerified email at aalto.fi

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 Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Data augmentation generative adversarial networks A Antoniou, A Storkey, H Edwards arXiv preprint arXiv:1711.04340, 2017	407	2017
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	386	2005
Exploration by random network distillation Y Burda, H Edwards, A Storkey, O Klimov arXiv preprint arXiv:1810.12894, 2018	289	2018
Censoring Representations with an Adversary H Edwards, A Storkey Proceedings of ICLR and arXiv preprint arXiv:1511.05897, 2015	266	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	256	2018
Towards a neural statistician H Edwards, A Storkey arXiv preprint arXiv:1606.02185, 2016	238	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	203	2006
When training and test sets are different: characterizing learning transfer A Storkey Dataset shift in machine learning, 3-28, 2009	193	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	176	2017
How to train your MAML A Antoniou, H Edwards, A Storkey arXiv preprint arXiv:1810.09502, 2018	145	2018
Training deep convolutional neural networks to play go C Clark, A Storkey arXiv:1412.3409, 2014, and Proceedings of the 32nd International Conference …, 2014	136	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	126	2014
The basins of attraction of a new Hopfield learning rule AJ Storkey, R Valabregue Neural Networks 12 (6), 869-876, 1999	103	1999
Mixture regression for covariate shift AJ Storkey, M Sugiyama Advances in Neural Information Processing Systems, 1337-1344, 2006	99*	2006
Probabilistic inference for solving (PO)MDPs M Toussaint, S Harmeling, A Storkey School of Informatics Technical Report, 2006	94	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	93	2011
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	85	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	79	2007
Meta-learning in neural networks: A survey T Hospedales, A Antoniou, P Micaelli, A Storkey arXiv preprint arXiv:2004.05439, 2020	73	2020
CINIC-10 is not ImageNet or CIFAR-10 LN Darlow, EJ Crowley, A Antoniou, AJ Storkey arXiv preprint arXiv:1810.03505, 2018	63	2018

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