Amos J. Storkey

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 111

Top Venues

Publications

Dongge Han, Trevor McInroe, Adam Jelley, Stefano V. Albrecht, Peter Bell, Amos J. Storkey
LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots. CoRR (2024)
Thomas L. Lee, Sigrid Passano Hellan, Linus Ericsson, Elliot J. Crowley, Amos J. Storkey
Hyperparameter Selection in Continual Learning. CoRR (2024)
Luke Nicholas Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos J. Storkey
DAM: Towards A Foundation Model for Time Series Forecasting. CoRR (2024)
Jamie Burke, Justin Engelmann, Charlene Hamid, Diana Moukaddem, Dan Pugh, Neeraj Dhaun, Amos J. Storkey, Niall C. Strang, Stuart King, Tom J. MacGillivray, Miguel O. Bernabeu, Ian J. C. MacCormick
Domain-specific augmentations with resolution agnostic self-attention mechanism improves choroid segmentation in optical coherence tomography images. CoRR (2024)
Luke Nicholas Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos J. Storkey
DAM: Towards a Foundation Model for Forecasting. ICLR (2024)
Adam Jelley, Trevor McInroe, Sam Devlin, Amos J. Storkey
Efficient Offline Reinforcement Learning: The Critic is Critical. CoRR (2024)
Linus Ericsson, Miguel Espinosa, Chenhongyi Yang, Antreas Antoniou, Amos J. Storkey, Shay B. Cohen, Steven McDonagh, Elliot J. Crowley
einspace: Searching for Neural Architectures from Fundamental Operations. CoRR (2024)
Thomas L. Lee, Amos J. Storkey
Approximate Bayesian Class-Conditional Models under Continuous Representation Shift. AISTATS (2024)
Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos J. Storkey, Tim Pearce, François Fleuret
Diffusion for World Modeling: Visual Details Matter in Atari. CoRR (2024)
Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
Contrastive Meta-Learning for Partially Observable Few-Shot Learning. CoRR (2023)
Alessandro Fontanella, Antreas Antoniou, Wenwen Li, Joanna M. Wardlaw, Grant Mair, Emanuele Trucco, Amos J. Storkey
ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. ICML (2023)
Asif Khan, Amos J. Storkey
Adversarial robustness of VAEs through the lens of local geometry. AISTATS (2023)
Trevor McInroe, Stefano V. Albrecht, Amos J. Storkey
Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning. CoRR (2023)
Alessandro Fontanella, Wenwen Li, Grant Mair, Antreas Antoniou, Eleanor Platt, Paul A. Armitage, Emanuele Trucco, Joanna M. Wardlaw, Amos J. Storkey
Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT. CoRR (2023)
Alessandro Fontanella, Grant Mair, Joanna M. Wardlaw, Emanuele Trucco, Amos J. Storkey
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images. CoRR (2023)
Jamie Burke, Justin Engelmann, Charlene Hamid, Megan Reid-Schachter, Tom Pearson, Dan Pugh, Neeraj Dhaun, Stuart King, Tom J. MacGillivray, Miguel O. Bernabeu, Amos J. Storkey, Ian J. C. MacCormick
Efficient and fully-automatic retinal choroid segmentation in OCT through DL-based distillation of a hand-crafted pipeline. CoRR (2023)
William Toner, Amos J. Storkey
Label Noise: Correcting a Correction. CoRR (2023)
Asif Khan, Amos J. Storkey
Contrastive Learning for Non-Local Graphs with Multi-Resolution Structural Views. CoRR (2023)
Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
Contrastive Meta-Learning for Partially Observable Few-Shot Learning. ICLR (2023)
Alessandro Fontanella, Antreas Antoniou, Wenwen Li, Joanna M. Wardlaw, Grant Mair, Emanuele Trucco, Amos J. Storkey
ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. CoRR (2023)
Thomas L. Lee, Amos J. Storkey
Chunking: Forgetting Matters in Continual Learning even without Changing Tasks. CoRR (2023)
Justin Engelmann, Amos J. Storkey, Miguel O. Bernabeu
QuickQual: Lightweight, convenient retinal image quality scoring with off-the-shelf pretrained models. CoRR (2023)
Perry Gibson, José Cano, Elliot J. Crowley, Amos J. Storkey, Michael F. P. O'Boyle
DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack. CoRR (2023)
Justin Engelmann, Jamie Burke, Charlene Hamid, Megan Reid-Schachter, Dan Pugh, Neeraj Dhaun, Diana Moukaddem, Lyle Gray, Niall C. Strang, Paul McGraw, Amos J. Storkey, Paul J. Steptoe, Stuart King, Tom J. MacGillivray, Miguel O. Bernabeu, Ian J. C. MacCormick
Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography. CoRR (2023)
Joseph Mellor, Wenhua Jiang, Alan Fleming, Stuart J. McGurnaghan, Luke Blackbourn, Caroline Styles, Amos J. Storkey, Paul McKeigue, Helen M. Colhoun
Can deep learning on retinal images augment known risk factors for cardiovascular disease prediction in diabetes? A prospective cohort study from the national screening programme in Scotland. Int. J. Medical Informatics 175 (2023)
Mateusz Ochal, Massimiliano Patacchiola, Jose Vazquez, Amos J. Storkey, Sen Wang
Few-Shot Learning With Class Imbalance. IEEE Trans. Artif. Intell. 4 (5) (2023)
Justin Engelmann, Amos J. Storkey, Miguel O. Bernabeu
QuickQual: Lightweight, Convenient Retinal Image Quality Scoring with Off-the-Shelf Pretrained Models. OMIA@MICCAI (2023)
Thomas L. Lee, Amos J. Storkey
Class Conditional Gaussians for Continual Learning. CoRR (2023)
Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos J. Storkey, Miguel O. Bernabeu
Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning. Nat. Mac. Intell. 4 (12) (2022)
Justin Engelmann, Ana Villaplana-Velasco, Amos J. Storkey, Miguel O. Bernabeu
Robust and efficient computation of retinal fractal dimension through deep approximation. CoRR (2022)
Chenhongyi Yang, Mateusz Ochal, Amos J. Storkey, Elliot J. Crowley
Prediction-Guided Distillation for Dense Object Detection. CoRR (2022)
Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos J. Storkey, Miguel O. Bernabeu
Detection of multiple retinal diseases in ultra-widefield fundus images using deep learning: data-driven identification of relevant regions. CoRR (2022)
Alex Horton, Martin Ewart, Noel Gourmelen, Xavier Fettweis, Amos J. Storkey
Using Deep Learning to Model Elevation Differences between Radar and Laser Altimetry. Remote. Sens. 14 (24) (2022)
Justin Engelmann, Ana Villaplana-Velasco, Amos J. Storkey, Miguel O. Bernabeu
Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation. OMIA@MICCAI (2022)
Asif Khan, Amos J. Storkey
Adversarial robustness of β-VAE through the lens of local geometry. CoRR (2022)
Chenhongyi Yang, Mateusz Ochal, Amos J. Storkey, Elliot J. Crowley
Prediction-Guided Distillation for Dense Object Detection. ECCV (9) (2022)
Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, Amos J. Storkey
Meta-Learning in Neural Networks: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Lukas Schäfer, Filippos Christianos, Amos J. Storkey, Stefano V. Albrecht
Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learning. CoRR (2022)
Bryan M. Li, Leonardo V. Castorina, Maria del C. Valdés Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael J. Thrippleton, Michael S. Stringer, Joanna M. Wardlaw
Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols. Frontiers Comput. Neurosci. 16 (2022)
Asif Khan, Amos J. Storkey
Hamiltonian Latent Operators for content and motion disentanglement in image sequences. NeurIPS (2022)
Mateusz Ochal, Massimiliano Patacchiola, Amos J. Storkey, Jose Vazquez, Sen Wang
How Sensitive are Meta-Learners to Dataset Imbalance? CoRR (2021)
Elliot J. Crowley, Gavin Gray, Jack Turner, Amos J. Storkey
Substituting Convolutions for Neural Network Compression. IEEE Access 9 (2021)
Justin Engelmann, Amos J. Storkey, Miguel O. Bernabeu
Global explainability in aligned image modalities. CoRR (2021)
Joe Mellor, Jack Turner, Amos J. Storkey, Elliot J. Crowley
Neural Architecture Search without Training. ICML (2021)
Paul Micaelli, Amos J. Storkey
Gradient-based Hyperparameter Optimization Over Long Horizons. NeurIPS (2021)
Benedict J. Leimkuhler, Tiffany J. Vlaar, Timothée Pouchon, Amos J. Storkey
Better Training using Weight-Constrained Stochastic Dynamics. ICML (2021)
Benedict J. Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos J. Storkey
Better Training using Weight-Constrained Stochastic Dynamics. CoRR (2021)
Asif Khan, Amos J. Storkey
Hamiltonian prior to Disentangle Content and Motion in Image Sequences. CoRR (2021)
Mateusz Ochal, Massimiliano Patacchiola, Amos J. Storkey, Jose Vazquez, Sen Wang
Few-Shot Learning with Class Imbalance. CoRR (2021)
Paul Micaelli, Amos J. Storkey
Non-greedy Gradient-based Hyperparameter Optimization Over Long Horizons. CoRR (2020)
Benedict J. Leimkuhler, Timothée Pouchon, Tiffany Vlaar, Amos J. Storkey
Constraint-Based Regularization of Neural Networks. CoRR (2020)
Valentin Radu, Kuba Kaszyk, Yuan Wen, Jack Turner, José Cano, Elliot J. Crowley, Björn Franke, Amos J. Storkey, Michael F. P. O'Boyle
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs. CoRR (2020)
Perry Gibson, José Cano, Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey
Optimizing Grouped Convolutions on Edge Devices. ASAP (2020)
Luke Nicholas Darlow, Amos J. Storkey
DHOG: Deep Hierarchical Object Grouping. CoRR (2020)
Joseph Charles Mellor, Jack Turner, Amos J. Storkey, Elliot J. Crowley
Neural Architecture Search without Training. CoRR (2020)
Luke Nicholas Darlow, Stanislaw Jastrzebski, Amos J. Storkey
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks. CoRR (2020)
Massimiliano Patacchiola, Amos J. Storkey
Self-Supervised Relational Reasoning for Representation Learning. CoRR (2020)
Luke Nicholas Darlow, Amos J. Storkey
What Information Does a ResNet Compress? CoRR (2020)
Antreas Antoniou, Massimiliano Patacchiola, Mateusz Ochal, Amos J. Storkey
Defining Benchmarks for Continual Few-Shot Learning. CoRR (2020)
Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey, Gavin Gray
BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget. ICLR (2020)
Stathi Fotiadis, Eduardo Pignatelli, Mario Lino Valencia, Chris D. Cantwell, Amos J. Storkey, Anil A. Bharath
Comparing recurrent and convolutional neural networks for predicting wave propagation. CoRR (2020)
Perry Gibson, José Cano, Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey
Optimizing Grouped Convolutions on Edge Devices. CoRR (2020)
Massimiliano Patacchiola, Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels. NeurIPS (2020)
Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, Amos J. Storkey
Meta-Learning in Neural Networks: A Survey. CoRR (2020)
Massimiliano Patacchiola, Amos J. Storkey
Self-Supervised Relational Reasoning for Representation Learning. NeurIPS (2020)
Paul Micaelli, Amos J. Storkey
Zero-shot Knowledge Transfer via Adversarial Belief Matching. NeurIPS (2019)
Yuri Burda, Harrison Edwards, Deepak Pathak, Amos J. Storkey, Trevor Darrell, Alexei A. Efros
Large-Scale Study of Curiosity-Driven Learning. ICLR (Poster) (2019)
Valentin Radu, Kuba Kaszyk, Yuan Wen, Jack Turner, José Cano, Elliot J. Crowley, Björn Franke, Amos J. Storkey, Michael F. P. O'Boyle
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs. IISWC (2019)
Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. ICLR (Poster) (2019)
Antreas Antoniou, Amos J. Storkey
Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation. CoRR (2019)
Jack Turner, Elliot J. Crowley, Gavin Gray, Amos J. Storkey, Michael F. P. O'Boyle
BlockSwap: Fisher-guided Block Substitution for Network Compression. CoRR (2019)
Antreas Antoniou, Amos J. Storkey
Learning to learn via Self-Critique. CoRR (2019)
Antreas Antoniou, Amos J. Storkey
Learning to Learn By Self-Critique. NeurIPS (2019)
Massimiliano Patacchiola, Jack Turner, Elliot J. Crowley, Amos J. Storkey
Deep Kernel Transfer in Gaussian Processes for Few-shot Learning. CoRR (2019)
Yuri Burda, Harrison Edwards, Amos J. Storkey, Oleg Klimov
Exploration by random network distillation. ICLR (Poster) (2019)
Gavin Gray, Elliot J. Crowley, Amos J. Storkey
Separable Layers Enable Structured Efficient Linear Substitutions. CoRR (2019)
Antreas Antoniou, Harrison Edwards, Amos J. Storkey
How to train your MAML. ICLR (Poster) (2019)
Paul Micaelli, Amos J. Storkey
Zero-shot Knowledge Transfer via Adversarial Belief Matching. CoRR (2019)
Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
DNN's Sharpest Directions Along the SGD Trajectory. CoRR (2018)
Antreas Antoniou, Harrison Edwards, Amos J. Storkey
How to train your MAML. CoRR (2018)
Elliot J. Crowley, Gavin Gray, Amos J. Storkey
Moonshine: Distilling with Cheap Convolutions. NeurIPS (2018)
Luke Nicholas Darlow, Elliot J. Crowley, Antreas Antoniou, Amos J. Storkey
CINIC-10 is not ImageNet or CIFAR-10. CoRR (2018)
Yuri Burda, Harrison Edwards, Deepak Pathak, Amos J. Storkey, Trevor Darrell, Alexei A. Efros
Large-Scale Study of Curiosity-Driven Learning. CoRR (2018)
Yuri Burda, Harrison Edwards, Amos J. Storkey, Oleg Klimov
Exploration by Random Network Distillation. CoRR (2018)
Jack Turner, José Cano, Valentin Radu, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey
Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks. CoRR (2018)
Jack Turner, José Cano, Valentin Radu, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey
Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks. IISWC (2018)
Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) (2018)
Antreas Antoniou, Agnieszka Slowik, Elliot J. Crowley, Amos J. Storkey
Dilated DenseNets for Relational Reasoning. CoRR (2018)
Luke Nicholas Darlow, Amos J. Storkey
GINN: Geometric Illustration of Neural Networks. CoRR (2018)
Elliot J. Crowley, Jack Turner, Amos J. Storkey, Michael F. P. O'Boyle
Pruning neural networks: is it time to nip it in the bud? CoRR (2018)
Antreas Antoniou, Amos J. Storkey, Harrison Edwards
Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks. ICANN (3) (2018)
Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
Finding Flatter Minima with SGD. ICLR (Workshop) (2018)
Jack Turner, Elliot J. Crowley, Valentin Radu, José Cano, Amos J. Storkey, Michael F. P. O'Boyle
HAKD: Hardware Aware Knowledge Distillation. CoRR (2018)
Tim Llewellynn, Maria del Milagro Fernández-Carrobles, Oscar Déniz, Samuel Fricker, Amos J. Storkey, Nuria Pazos, Gordana Velikic, Kirsten Leufgen, Rozenn Dahyot, Sebastian Koller, Georgios I. Goumas, Peter Leitner, Ganesh Dasika, Lei Wang, Kurt Tutschku
BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited paper. Conf. Computing Frontiers (2017)
Matthew M. Graham, Amos J. Storkey
Asymptotically exact inference in differentiable generative models. AISTATS (2017)
Harrison Edwards, Amos J. Storkey
Towards a Neural Statistician. ICLR (Poster) (2017)
Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
Three Factors Influencing Minima in SGD. CoRR (2017)
Elliot J. Crowley, Gavin Gray, Amos J. Storkey
Moonshine: Distilling with Cheap Convolutions. CoRR (2017)
Antreas Antoniou, Amos J. Storkey, Harrison Edwards
Data Augmentation Generative Adversarial Networks. CoRR (2017)
Matthew M. Graham, Amos J. Storkey
Continuously Tempered Hamiltonian Monte Carlo. UAI (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Amos J. Storkey