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D-Index & Metrics

Computer Science

D-Index
48
Citations
29656
World Ranking
5996
National Ranking
364

Overview

Amos Storkey is affiliated with the University of Edinburgh in the United Kingdom. Their research spans multiple fields, primarily focusing on Computer Science and Medicine. Within these broad disciplines, Storkey has significantly contributed to subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Ophthalmology, and Biomedical Engineering.

The scientist's work is oriented around several main topics, including Domain Adaptation and Few-Shot Learning, Retinal Imaging and Analysis, Advanced Neural Network Applications, Machine Learning and Data Classification, Retinal Diseases and Treatments, Adversarial Robustness in Machine Learning, and Multimodal Machine Learning Applications.

Storkey has published numerous papers, with some recent examples illustrating the diversity of their research interests. These include:

  • "Meta-Learning in Neural Networks: A Survey" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Obstructing Classification via Projection" (2021), published in Dagstuhl Research Online Publication Server
  • "Large-Scale Study of Curiosity-Driven Learning" (2025), published on arXiv (Cornell University)
  • "Accuracy of Automated Computer-Aided Diagnosis for Stroke Imaging: A Critical Evaluation of Current Evidence" (2022), published in Stroke
  • "Neural Architecture Search without Training" (2020), published on arXiv (Cornell University)

The publication venues where Storkey most frequently appears include arXiv (Cornell University), with 49 papers, alongside multiple contributions to the British Journal of Ophthalmology, IEEE Transactions on Pattern Analysis and Machine Intelligence, Dagstuhl Research Online Publication Server, and Stroke.

Collaboration is also a noticeable aspect of Storkey's research, with frequent co-authors including Justin Engelmann, Miguel O. Bernabéu, Joanna M. Wardlaw, Elliot J. Crowley, and Grant Mair, each having coauthored multiple papers with Storkey.

Best Publications

  • Advances in Neural Information Processing Systems 25

    Yichuan Zhang;Charles Sutton;Amos Storkey;Zoubin Ghahramani

  • Meta-Learning in Neural Networks: A Survey.

    Timothy M Hospedales;Antreas Antoniou;Paul Micaelli;Amos J. Storkey

  • Data Augmentation Generative Adversarial Networks

    Antreas Antoniou;Amos J. Storkey;Harrison Edwards

  • Advances in Neural Information Processing Systems 19 (NIPS 2006)

    Enrico Simonotto;Heather Whalley;Stephen Lawrie;Lawrence Murray

  • Exploration by random network distillation

    Yuri Burda;Harrison Edwards;Amos J. Storkey;Oleg Klimov

  • The 2005 PASCAL visual object classes challenge

    Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

  • Probabilistic inference for solving discrete and continuous state Markov Decision Processes

    Marc Toussaint;Amos Storkey

  • Large-Scale Study of Curiosity-Driven Learning

    Yuri Burda;Harrison Edwards;Deepak Pathak;Amos J. Storkey

  • Censoring Representations with an Adversary

    Harrison Edwards;Amos Storkey

  • Three Factors Influencing Minima in SGD

    Stanislaw Jastrzebski;Zachary Kenton;Devansh Arpit;Nicolas Ballas

  • ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16

    Amos Storkey

  • Towards a Neural Statistician

    Harrison Edwards;Amos J. Storkey

  • How to train your MAML

    Antreas Antoniou;Harrison Edwards;Amos J. Storkey

  • Extracting Motion Primitives from Natural Handwriting Data

    Ben H. Williams;Marc Toussaint;Amos J. Storkey

  • When Training and Test Sets are Different: Characterising Learning Transfer

    Amos J Storkey

  • Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks

    Antreas Antoniou;Amos J. Storkey;Harrison Edwards

  • Neural Information Processing Systems (NIPS)

    Xiaocheng Shang;Zhanxing Zhu;Benedict Leimkuhler;Amos Storkey

  • Test–retest reliability of structural brain networks from diffusion MRI

    Colin R. Buchanan;Cyril R. Pernet;Krzysztof J. Gorgolewski;Amos J. Storkey

  • Training Deep Convolutional Neural Networks to Play Go

    Christopher Clark;Amos Storkey

  • CINIC-10 Is Not ImageNet or CIFAR-10

    Luke Nicholas Darlow;Elliot J. Crowley;Antreas Antoniou;Amos J. Storkey

  • Neural Architecture Search without Training

    Joseph Mellor;Jack Turner;Amos Storkey;Elliot J. Crowley

Frequent Co-Authors

Mark E. Bastin
Mark E. Bastin University of Edinburgh
Michael F. P. O'Boyle
Michael F. P. O'Boyle University of Edinburgh
Krzysztof J. Gorgolewski
Krzysztof J. Gorgolewski Stanford University
Cyril Pernet
Cyril Pernet Copenhagen University Hospital
Yoshua Bengio
Yoshua Bengio University of Montreal
Marc Toussaint
Marc Toussaint Technical University of Berlin
Robert G. Mann
Robert G. Mann University of Edinburgh
Nicolas Ballas
Nicolas Ballas Facebook (United States)
Nigel Hambly
Nigel Hambly University of Edinburgh
Joanna M. Wardlaw
Joanna M. Wardlaw University of Edinburgh

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