Amos Storkey

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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. GorgolewskiGoogleVerified email at google.com
Cyril PernetSenior RSE, Neurobiology Research Unit, Copenhagen University Hospital, RigshospitaletVerified email at nru.dk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyVerified email at tu-berlin.de
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
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
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
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
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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Data augmentation generative adversarial networks A Antoniou, A Storkey, H Edwards arXiv preprint arXiv:1711.04340, 2017	503	2017
Exploration by random network distillation Y Burda, H Edwards, A Storkey, O Klimov arXiv preprint arXiv:1810.12894, 2018	391	2018
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	327	2018
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	307	2005
Censoring Representations with an Adversary H Edwards, A Storkey Proceedings of ICLR and arXiv preprint arXiv:1511.05897, 2015	302	2015
Towards a neural statistician H Edwards, A Storkey arXiv preprint arXiv:1606.02185, 2016	286	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	219	2006
How to train your maml A Antoniou, H Edwards, A Storkey arXiv preprint arXiv:1810.09502, 2018	213	2018
When training and test sets are different: characterizing learning transfer A Storkey Dataset shift in machine learning 30, 3-28, 2009	213	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	207	2017
Meta-learning in neural networks: A survey T Hospedales, A Antoniou, P Micaelli, A Storkey arXiv preprint arXiv:2004.05439, 2020	179	2020
Training deep convolutional neural networks to play go C Clark, A Storkey arXiv:1412.3409, 2014, and Proceedings of the 32nd International Conference …, 2014	143	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	132	2014
The basins of attraction of a new Hopfield learning rule AJ Storkey, R Valabregue Neural Networks 12 (6), 869-876, 1999	106	1999
Mixture regression for covariate shift AJ Storkey, M Sugiyama Advances in Neural Information Processing Systems, 1337-1344, 2006	105	2006
Probabilistic inference for solving (PO)MDPs M Toussaint, S Harmeling, A Storkey School of Informatics Technical Report, 2006	102	2006
TractoR: magnetic resonance imaging and tractography with R JD Clayden, S Muñoz Maniega, AJ Storkey, MD King, ME Bastin, ... Journal of Statistical Software 44 (8), 1-18, 2011	96	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	91	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	82	2007
Cinic-10 is not imagenet or cifar-10 LN Darlow, EJ Crowley, A Antoniou, AJ Storkey arXiv preprint arXiv:1810.03505, 2018	78	2018

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