Amos J. Storkey

Affiliations:
  • University of Edinburgh, UK


According to our database1, Amos J. Storkey authored at least 125 papers between 1996 and 2023.

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Bibliography

2023
Few-Shot Learning With Class Imbalance.
IEEE Trans. Artif. Intell., October, 2023

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, July, 2023

Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography.
CoRR, 2023

DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack.
CoRR, 2023

Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning.
CoRR, 2023

Chunking: Forgetting Matters in Continual Learning even without Changing Tasks.
CoRR, 2023

Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT.
CoRR, 2023

Contrastive Learning for Non-Local Graphs with Multi-Resolution Structural Views.
CoRR, 2023

Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images.
CoRR, 2023

Label Noise: Correcting a Correction.
CoRR, 2023

Efficient and fully-automatic retinal choroid segmentation in OCT through DL-based distillation of a hand-crafted pipeline.
CoRR, 2023

Class Conditional Gaussians for Continual Learning.
CoRR, 2023

QuickQual: Lightweight, Convenient Retinal Image Quality Scoring with Off-the-Shelf Pretrained Models.
Proceedings of the Ophthalmic Medical Image Analysis - 10th International Workshop, 2023

ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging.
Proceedings of the International Conference on Machine Learning, 2023

Contrastive Meta-Learning for Partially Observable Few-Shot Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Adversarial robustness of VAEs through the lens of local geometry.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Using Deep Learning to Model Elevation Differences between Radar and Laser Altimetry.
Remote. Sens., December, 2022

Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning.
Nat. Mac. Intell., December, 2022

Meta-Learning in Neural Networks: A Survey.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols.
Frontiers Comput. Neurosci., 2022

Adversarial robustness of β-VAE through the lens of local geometry.
CoRR, 2022

Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learning.
CoRR, 2022

Detection of multiple retinal diseases in ultra-widefield fundus images using deep learning: data-driven identification of relevant regions.
CoRR, 2022

Hamiltonian Latent Operators for content and motion disentanglement in image sequences.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation.
Proceedings of the Ophthalmic Medical Image Analysis - 9th International Workshop, 2022

Prediction-Guided Distillation for Dense Object Detection.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Global explainability in aligned image modalities.
CoRR, 2021

Hamiltonian Operator Disentanglement of Content and Motion in Image Sequences.
CoRR, 2021

How Sensitive are Meta-Learners to Dataset Imbalance?
CoRR, 2021

Substituting Convolutions for Neural Network Compression.
IEEE Access, 2021

Gradient-based Hyperparameter Optimization Over Long Horizons.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Architecture Search without Training.
Proceedings of the 38th International Conference on Machine Learning, 2021

Better Training using Weight-Constrained Stochastic Dynamics.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks.
CoRR, 2020

Non-greedy Gradient-based Hyperparameter Optimization Over Long Horizons.
CoRR, 2020

Constraint-Based Regularization of Neural Networks.
CoRR, 2020

Neural Architecture Search without Training.
CoRR, 2020

Defining Benchmarks for Continual Few-Shot Learning.
CoRR, 2020

DHOG: Deep Hierarchical Object Grouping.
CoRR, 2020

What Information Does a ResNet Compress?
CoRR, 2020

Comparing recurrent and convolutional neural networks for predicting wave propagation.
CoRR, 2020

Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Self-Supervised Relational Reasoning for Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget.
Proceedings of the 8th International Conference on Learning Representations, 2020

Optimizing Grouped Convolutions on Edge Devices.
Proceedings of the 31st IEEE International Conference on Application-specific Systems, 2020

2019
Deep Kernel Transfer in Gaussian Processes for Few-shot Learning.
CoRR, 2019

BlockSwap: Fisher-guided Block Substitution for Network Compression.
CoRR, 2019

Separable Layers Enable Structured Efficient Linear Substitutions.
CoRR, 2019

Learning to learn via Self-Critique.
CoRR, 2019

Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation.
CoRR, 2019

Zero-shot Knowledge Transfer via Adversarial Belief Matching.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Learn By Self-Critique.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs.
Proceedings of the IEEE International Symposium on Workload Characterization, 2019

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length.
Proceedings of the 7th International Conference on Learning Representations, 2019

Exploration by random network distillation.
Proceedings of the 7th International Conference on Learning Representations, 2019

Large-Scale Study of Curiosity-Driven Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

How to train your MAML.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Dilated DenseNets for Relational Reasoning.
CoRR, 2018

HAKD: Hardware Aware Knowledge Distillation.
CoRR, 2018

Pruning neural networks: is it time to nip it in the bud?
CoRR, 2018

CINIC-10 is not ImageNet or CIFAR-10.
CoRR, 2018

GINN: Geometric Illustration of Neural Networks.
CoRR, 2018

DNN's Sharpest Directions Along the SGD Trajectory.
CoRR, 2018

Moonshine: Distilling with Cheap Convolutions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks.
Proceedings of the 2018 IEEE International Symposium on Workload Characterization, 2018

Finding Flatter Minima with SGD.
Proceedings of the 6th International Conference on Learning Representations, 2018

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017
Three Factors Influencing Minima in SGD.
CoRR, 2017

Data Augmentation Generative Adversarial Networks.
CoRR, 2017

Continuously Tempered Hamiltonian Monte Carlo.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Towards a Neural Statistician.
Proceedings of the 5th International Conference on Learning Representations, 2017

BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited paper.
Proceedings of the Computing Frontiers Conference, 2017

Asymptotically exact inference in differentiable generative models.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Evaluation of a pre-surgical functional MRI workflow: From data acquisition to reporting.
Int. J. Medical Informatics, 2016

Censoring Representations with an Adversary.
Proceedings of the 4th International Conference on Learning Representations, 2016

Stochastic Parallel Block Coordinate Descent for Large-Scale Saddle Point Problems.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
The Supervised Hierarchical Dirichlet Process.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Aggregation Under Bias: Rényi Divergence Aggregation and Its Implementation via Machine Learning Markets.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Training Deep Convolutional Neural Networks to Play Go.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Series Expansion Approximations of Brownian Motion for Non-Linear Kalman Filtering of Diffusion Processes.
IEEE Trans. Signal Process., 2014

Test-retest reliability of structural brain networks from diffusion MRI.
NeuroImage, 2014

Teaching Deep Convolutional Neural Networks to Play Go.
CoRR, 2014

Multi-period Trading Prediction Markets with Connections to Machine Learning.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex?
PLoS Comput. Biol., 2013

Single subject fMRI test-retest reliability metrics and confounding factors.
NeuroImage, 2013

Bayesian Inference in Sparse Gaussian Graphical Models.
CoRR, 2013

2012
Discriminative Mixtures of Sparse Latent Fields for Risk Management.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Continuous Relaxations for Discrete Hamiltonian Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Isoelastic Agents and Wealth Updates in Machine Learning Markets.
Proceedings of the 29th International Conference on Machine Learning, 2012

A Topic Model for Melodic Sequences.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Particle Smoothing in Continuous Time: A Fast Approach via Density Estimation.
IEEE Trans. Signal Process., 2011

Machine Learning Markets.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Comparing Probabilistic Models for Melodic Sequences.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A Hierarchical Generative Model of Recurrent Object-Based Attention in the Visual Cortex.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

The Grouped Author-Topic Model for Unsupervised Entity Resolution.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010
Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Sparse Instrumental Variables (SPIV) for Genome-Wide Studies.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Reproducibility of tract segmentation between sessions using an unsupervised modelling-based approach.
NeuroImage, 2009

2008
Tract shape modelling provides evidence of topological change in corpus callosum genu during normal ageing.
NeuroImage, 2008

2007
A Probabilistic Model-Based Approach to Consistent White Matter Tract Segmentation.
IEEE Trans. Medical Imaging, 2007

Modelling motion primitives and their timing in biologically executed movements.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Continuous Time Particle Filtering for fMRI.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Primitive Based Generative Model to Infer Timing Information in Unpartitioned Handwriting Data.
Proceedings of the IJCAI 2007, 2007

2006
Improved segmentation reproducibility in group tractography using a quantitative tract similarity measure.
NeuroImage, 2006

Learning Structural Equation Models for fMRI.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Mixture Regression for Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Probabilistic inference for solving discrete and continuous state Markov Decision Processes.
Proceedings of the Machine Learning, 2006

Extracting Motion Primitives from Natural Handwriting Data.
Proceedings of the Artificial Neural Networks, 2006

2005

2004
Cosine Transform Priors for Enhanced Decoding of Compressed Images.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2004

2003
Image Modeling with Position-Encoding Dynamic Trees.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Renewal Strings for Cleaning Astronomical Databases.
Proceedings of the UAI '03, 2003

Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Dynamic Structure Super-Resolution.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
Dynamic Positional Trees for Structural Image Analysis.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

MFDTs: Mean Field Dynamic Trees.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

1999
The basins of attraction of a new Hopfield learning rule.
Neural Networks, 1999

1997
Increasing the Capacity of a Hopfield Network without Sacrificing Functionality.
Proceedings of the Artificial Neural Networks, 1997

1996
A Modified Spreading Algorithm for Autoassociation in Weightless Neural Networks.
Proceedings of the Artificial Neural Networks, 1996


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