Amos Storkey
Amos Storkey
Professor of Machine Learning and AI, School of Informatics, University of Edinburgh, UK
Verified email at ed.ac.uk
Title
Cited by
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
10065*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
2802005
Data augmentation generative adversarial networks
A Antoniou, A Storkey, H Edwards
arXiv preprint arXiv:1711.04340, 2017
2282017
Censoring Representations with an Adversary
H Edwards, A Storkey
Proceedings of ICLR and arXiv preprint arXiv:1511.05897, 2015
1732015
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
1732006
Towards a neural statistician
H Edwards, A Storkey
arXiv preprint arXiv:1606.02185, 2016
1712016
Training deep convolutional neural networks to play go
C Clark, A Storkey
arXiv:1412.3409, 2014, and Proceedings of the 32nd International Conference …, 2014
1652014
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
1472018
When training and test sets are different: characterizing learning transfer
A Storkey
Dataset shift in machine learning, 3-28, 2009
1402009
Exploration by random network distillation
Y Burda, H Edwards, A Storkey, O Klimov
arXiv preprint arXiv:1810.12894, 2018
1322018
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
1072017
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
1062014
The basins of attraction of a new Hopfield learning rule
AJ Storkey, R Valabregue
Neural Networks 12 (6), 869-876, 1999
1001999
Probabilistic inference for solving (PO)MDPs
M Toussaint, S Harmeling, A Storkey
School of Informatics Technical Report, 2006
912006
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
872011
Mixture regression for covariate shift
AJ Storkey, M Sugiyama
Advances in Neural Information Processing Systems, 1337-1344, 2006
81*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
772007
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
752013
How to train your maml
A Antoniou, H Edwards, A Storkey
arXiv preprint arXiv:1810.09502, 2018
632018
Increasing the capacity of a Hopfield network without sacrificing functionality
A Storkey
International Conference on Artificial Neural Networks, 451-456, 1997
591997
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