Amos J. Storkey

142 papers A* 20A 9B 2C 3Journal 76Unranked 32

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adapting Time Series Foundation Models through Data Mixtures. CoRR Thomas L. Lee, Edoardo M. Ponti, Amos J. Storkey
2026	J	`jnl`	Kalman Linear Attention: Parallel Bayesian Filtering For Efficient Language Modelling and State Tracking. CoRR Vaisakh Shaj, Cameron Barker, Aidan Scannell, Andras Szecsenyi, Elliot J. Crowley, Amos J. Storkey
2026	—	`conf`	On Harnessing Idle Compute at the Edge for Foundation Model Training. EuroMLSys@EuroSys Leyang Xue, Meghana Madhyastha, Myungjin Lee, Amos J. Storkey, Randal C. Burns, Mahesh K. Marina
2026	J	`jnl`	Probing Dec-POMDP Reasoning in Cooperative MARL. CoRR Kale-ab Abebe Tessera, Leonard Hinckeldey, Riccardo Zamboni, David Abel, Amos J. Storkey
2026	J	`jnl`	Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting. CoRR Benjamin R. Redhead, Thomas L. Lee, Peng Gu, Víctor Elvira, Amos J. Storkey
2025	B	`conf`	LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots. COLING Dongge Han, Trevor McInroe, Adam Jelley, Stefano V. Albrecht, Peter Bell, Amos J. Storkey
2025	J	`jnl`	Objects matter: object-centric world models improve reinforcement learning in visually complex environments. CoRR Weipu Zhang, Adam Jelley, Trevor McInroe, Amos J. Storkey
2025	J	`jnl`	On Harnessing Idle Compute at the Edge for Foundation Model Training. CoRR Leyang Xue, Meghana Madhyastha, Myungjin Lee, Amos J. Storkey, Randal C. Burns, Mahesh K. Marina
2024	A	`conf`	Approximate Bayesian Class-Conditional Models under Continuous Representation Shift. AISTATS Thomas L. Lee, Amos J. Storkey
2024	J	`jnl`	DAM: Towards A Foundation Model for Time Series Forecasting. CoRR Luke Nicholas Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos J. Storkey
2024	A*	`conf`	DAM: Towards a Foundation Model for Forecasting. ICLR Luke Nicholas Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos J. Storkey
2024	A*	`conf`	Diffusion for World Modeling: Visual Details Matter in Atari. NeurIPS Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos J. Storkey, Tim Pearce, François Fleuret
2024	J	`jnl`	Diffusion for World Modeling: Visual Details Matter in Atari. CoRR Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos J. Storkey, Tim Pearce, François Fleuret
2024	J	`jnl`	Domain-specific augmentations with resolution agnostic self-attention mechanism improves choroid segmentation in optical coherence tomography images. CoRR 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
2024	J	`jnl`	Efficient Offline Reinforcement Learning: The Critic is Critical. CoRR Adam Jelley, Trevor McInroe, Sam Devlin, Amos J. Storkey
2024	J	`jnl`	LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots. CoRR Dongge Han, Trevor McInroe, Adam Jelley, Stefano V. Albrecht, Peter Bell, Amos J. Storkey
2024	J	`jnl`	Noisy Early Stopping for Noisy Labels. CoRR William Toner, Amos J. Storkey
2024	J	`jnl`	Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning. RLJ Trevor McInroe, Adam Jelley, Stefano V. Albrecht, Amos J. Storkey
2024	—	`conf`	Pre-processing and Quality Control of Large Clinical CT Head Datasets for Intracranial Arterial Calcification Segmentation. DEMI@MICCAI Benjamin Jin, Maria del C. Valdés Hernández, Alessandro Fontanella, Wenwen Li, Eleanor Platt, Paul A. Armitage, Amos J. Storkey, Joanna M. Wardlaw, Grant Mair
2023	A*	`conf`	ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. ICML Alessandro Fontanella, Antreas Antoniou, Wenwen Li, Joanna M. Wardlaw, Grant Mair, Emanuele Trucco, Amos J. Storkey
2023	J	`jnl`	ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. CoRR Alessandro Fontanella, Antreas Antoniou, Wenwen Li, Joanna M. Wardlaw, Grant Mair, Emanuele Trucco, Amos J. Storkey
2023	J	`jnl`	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 Joseph Mellor, Wenhua Jiang, Alan Fleming, Stuart J. McGurnaghan, Luke Blackbourn, Caroline Styles, Amos J. Storkey, Paul McKeigue, Helen M. Colhoun
2023	J	`jnl`	Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography. CoRR 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
2023	A*	`conf`	Contrastive Meta-Learning for Partially Observable Few-Shot Learning. ICLR Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
2023	J	`jnl`	Contrastive Meta-Learning for Partially Observable Few-Shot Learning. CoRR Adam Jelley, Amos J. Storkey, Antreas Antoniou, Sam Devlin
2023	J	`jnl`	Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT. CoRR Alessandro Fontanella, Wenwen Li, Grant Mair, Antreas Antoniou, Eleanor Platt, Paul A. Armitage, Emanuele Trucco, Joanna M. Wardlaw, Amos J. Storkey
2023	J	`jnl`	Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images. CoRR Alessandro Fontanella, Grant Mair, Joanna M. Wardlaw, Emanuele Trucco, Amos J. Storkey
2023	J	`jnl`	Efficient and fully-automatic retinal choroid segmentation in OCT through DL-based distillation of a hand-crafted pipeline. CoRR 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
2023	J	`jnl`	Label Noise: Correcting a Correction. CoRR William Toner, Amos J. Storkey
2023	J	`jnl`	Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning. CoRR Trevor McInroe, Stefano V. Albrecht, Amos J. Storkey
2023	—	`conf`	QuickQual: Lightweight, Convenient Retinal Image Quality Scoring with Off-the-Shelf Pretrained Models. OMIA@MICCAI Justin Engelmann, Amos J. Storkey, Miguel O. Bernabeu
2023	J	`jnl`	QuickQual: Lightweight, convenient retinal image quality scoring with off-the-shelf pretrained models. CoRR Justin Engelmann, Amos J. Storkey, Miguel O. Bernabeu
2022	J	`jnl`	Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols. Frontiers Comput. Neurosci. 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
2022	J	`jnl`	Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning. Nat. Mac. Intell. Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos J. Storkey, Miguel O. Bernabeu
2022	J	`jnl`	Detection of multiple retinal diseases in ultra-widefield fundus images using deep learning: data-driven identification of relevant regions. CoRR Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos J. Storkey, Miguel O. Bernabeu
2022	A*	`conf`	Hamiltonian Latent Operators for content and motion disentanglement in image sequences. NeurIPS Asif Khan, Amos J. Storkey
2022	J	`jnl`	Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learning. CoRR Lukas Schäfer, Filippos Christianos, Amos J. Storkey, Stefano V. Albrecht
2022	—	`conf`	Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation. OMIA@MICCAI Justin Engelmann, Ana Villaplana-Velasco, Amos J. Storkey, Miguel O. Bernabeu
2022	J	`jnl`	Robust and efficient computation of retinal fractal dimension through deep approximation. CoRR Justin Engelmann, Ana Villaplana-Velasco, Amos J. Storkey, Miguel O. Bernabeu
2022	J	`jnl`	Using Deep Learning to Model Elevation Differences between Radar and Laser Altimetry. Remote. Sens. Alex Horton, Martin Ewart, Noel Gourmelen, Xavier Fettweis, Amos J. Storkey
2021	A*	`conf`	Better Training using Weight-Constrained Stochastic Dynamics. ICML Benedict J. Leimkuhler, Tiffany J. Vlaar, Timothée Pouchon, Amos J. Storkey
2021	J	`jnl`	Better Training using Weight-Constrained Stochastic Dynamics. CoRR Benedict J. Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos J. Storkey
2021	J	`jnl`	Few-Shot Learning with Class Imbalance. CoRR Mateusz Ochal, Massimiliano Patacchiola, Amos J. Storkey, Jose Vazquez, Sen Wang
2021	J	`jnl`	Global explainability in aligned image modalities. CoRR Justin Engelmann, Amos J. Storkey, Miguel O. Bernabeu
2021	A*	`conf`	Gradient-based Hyperparameter Optimization Over Long Horizons. NeurIPS Paul Micaelli, Amos J. Storkey
2021	J	`jnl`	How Sensitive are Meta-Learners to Dataset Imbalance? CoRR Mateusz Ochal, Massimiliano Patacchiola, Amos J. Storkey, Jose Vazquez, Sen Wang
2020	A*	`conf`	Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels. NeurIPS Massimiliano Patacchiola, Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey
2020	J	`jnl`	Comparing recurrent and convolutional neural networks for predicting wave propagation. CoRR Stathi Fotiadis, Eduardo Pignatelli, Mario Lino Valencia, Chris D. Cantwell, Amos J. Storkey, Anil A. Bharath
2020	J	`jnl`	Constraint-Based Regularization of Neural Networks. CoRR Benedict J. Leimkuhler, Timothée Pouchon, Tiffany Vlaar, Amos J. Storkey
2020	J	`jnl`	DHOG: Deep Hierarchical Object Grouping. CoRR Luke Nicholas Darlow, Amos J. Storkey
2020	J	`jnl`	Defining Benchmarks for Continual Few-Shot Learning. CoRR Antreas Antoniou, Massimiliano Patacchiola, Mateusz Ochal, Amos J. Storkey
2020	J	`jnl`	Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks. CoRR Luke Nicholas Darlow, Stanislaw Jastrzebski, Amos J. Storkey
2020	J	`jnl`	Meta-Learning in Neural Networks: A Survey. CoRR Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, Amos J. Storkey
2020	J	`jnl`	Non-greedy Gradient-based Hyperparameter Optimization Over Long Horizons. CoRR Paul Micaelli, Amos J. Storkey
2020	A*	`conf`	Self-Supervised Relational Reasoning for Representation Learning. NeurIPS Massimiliano Patacchiola, Amos J. Storkey
2020	J	`jnl`	Self-Supervised Relational Reasoning for Representation Learning. CoRR Massimiliano Patacchiola, Amos J. Storkey
2020	J	`jnl`	What Information Does a ResNet Compress? CoRR Luke Nicholas Darlow, Amos J. Storkey
2019	J	`jnl`	Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation. CoRR Antreas Antoniou, Amos J. Storkey
2019	—	`conf`	Exploration by random network distillation. ICLR (Poster) Yuri Burda, Harrison Edwards, Amos J. Storkey, Oleg Klimov
2019	—	`conf`	How to train your MAML. ICLR (Poster) Antreas Antoniou, Harrison Edwards, Amos J. Storkey
2019	—	`conf`	Large-Scale Study of Curiosity-Driven Learning. ICLR (Poster) Yuri Burda, Harri Edwards, Deepak Pathak, Amos J. Storkey, Trevor Darrell, Alexei A. Efros
2019	A*	`conf`	Learning to Learn By Self-Critique. NeurIPS Antreas Antoniou, Amos J. Storkey
2019	J	`jnl`	Learning to learn via Self-Critique. CoRR Antreas Antoniou, Amos J. Storkey
2019	—	`conf`	On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. ICLR (Poster) Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2019	A*	`conf`	Zero-shot Knowledge Transfer via Adversarial Belief Matching. NeurIPS Paul Micaelli, Amos J. Storkey
2019	J	`jnl`	Zero-shot Knowledge Transfer via Adversarial Belief Matching. CoRR Paul Micaelli, Amos J. Storkey
2018	—	`conf`	Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks. ICANN (3) Antreas Antoniou, Amos J. Storkey, Harrison Edwards
2018	J	`jnl`	CINIC-10 is not ImageNet or CIFAR-10. CoRR Luke Nicholas Darlow, Elliot J. Crowley, Antreas Antoniou, Amos J. Storkey
2018	J	`jnl`	DNN's Sharpest Directions Along the SGD Trajectory. CoRR Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2018	J	`jnl`	Exploration by Random Network Distillation. CoRR Yuri Burda, Harrison Edwards, Amos J. Storkey, Oleg Klimov
2018	—	`conf`	Finding Flatter Minima with SGD. ICLR (Workshop) Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2018	J	`jnl`	GINN: Geometric Illustration of Neural Networks. CoRR Luke Nicholas Darlow, Amos J. Storkey
2018	J	`jnl`	How to train your MAML. CoRR Antreas Antoniou, Harrison Edwards, Amos J. Storkey
2018	A	`ed.`	International Conference on Artificial Intelligence and Statistics, AISTATS 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, Spain AISTATS Amos J. Storkey, Fernando Pérez-Cruz
2018	J	`jnl`	Large-Scale Study of Curiosity-Driven Learning. CoRR Yuri Burda, Harri Edwards, Deepak Pathak, Amos J. Storkey, Trevor Darrell, Alexei A. Efros
2018	A*	`conf`	Moonshine: Distilling with Cheap Convolutions. NeurIPS Elliot J. Crowley, Gavin Gray, Amos J. Storkey
2018	—	`conf`	Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2017	A	`conf`	Asymptotically exact inference in differentiable generative models. AISTATS Matthew M. Graham, Amos J. Storkey
2017	—	`conf`	BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited paper. Conf. Computing Frontiers 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
2017	A	`conf`	Continuously Tempered Hamiltonian Monte Carlo. UAI Matthew M. Graham, Amos J. Storkey
2017	J	`jnl`	Data Augmentation Generative Adversarial Networks. CoRR Antreas Antoniou, Amos J. Storkey, Harrison Edwards
2017	J	`jnl`	Three Factors Influencing Minima in SGD. CoRR Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2017	—	`conf`	Towards a Neural Statistician. ICLR (Poster) Harrison Edwards, Amos J. Storkey
2016	A*	`conf`	Censoring Representations with an Adversary. ICLR (Poster) Harrison Edwards, Amos J. Storkey
2016	J	`jnl`	Evaluation of a pre-surgical functional MRI workflow: From data acquisition to reporting. Int. J. Medical Informatics Cyril R. Pernet, Krzysztof J. Gorgolewski, Dominic Job, David Rodriguez, Amos J. Storkey, Ian Whittle, Joanna M. Wardlaw
2016	A*	`conf`	Stochastic Parallel Block Coordinate Descent for Large-Scale Saddle Point Problems. AAAI Zhanxing Zhu, Amos J. Storkey
2016	J	`jnl`	Towards a Neural Statistician. CoRR Harrison Edwards, Amos J. Storkey
2015	—	`conf`	Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems. ECML/PKDD (1) Zhanxing Zhu, Amos J. Storkey
2015	J	`jnl`	Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems. CoRR Zhanxing Zhu, Amos J. Storkey
2015	—	`conf`	Aggregation Under Bias: Rényi Divergence Aggregation and Its Implementation via Machine Learning Markets. ECML/PKDD (1) Amos J. Storkey, Zhanxing Zhu, Jinli Hu
2015	—	`conf`	Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling. NIPS Xiaocheng Shang, Zhanxing Zhu, Benedict J. Leimkuhler, Amos J. Storkey
2015	J	`jnl`	Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling. CoRR Xiaocheng Shang, Zhanxing Zhu, Benedict J. Leimkuhler, Amos J. Storkey
2015	J	`jnl`	The Supervised Hierarchical Dirichlet Process. IEEE Trans. Pattern Anal. Mach. Intell. Andrew M. Dai, Amos J. Storkey
2015	A*	`conf`	Training Deep Convolutional Neural Networks to Play Go. ICML Christopher Clark, Amos J. Storkey
2014	A*	`conf`	Multi-period Trading Prediction Markets with Connections to Machine Learning. ICML Jinli Hu, Amos J. Storkey
2014	J	`jnl`	Multi-period Trading Prediction Markets with Connections to Machine Learning. CoRR Jinli Hu, Amos J. Storkey
2014	J	`jnl`	Renewal Strings for Cleaning Astronomical Databases. CoRR Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann
2014	J	`jnl`	Series Expansion Approximations of Brownian Motion for Non-Linear Kalman Filtering of Diffusion Processes. IEEE Trans. Signal Process. Simon M. J. Lyons, Simo Särkkä, Amos J. Storkey
2014	J	`jnl`	Teaching Deep Convolutional Neural Networks to Play Go. CoRR Christopher Clark, Amos J. Storkey
2014	J	`jnl`	Test-retest reliability of structural brain networks from diffusion MRI. NeuroImage Colin R. Buchanan, Cyril R. Pernet, Krzysztof J. Gorgolewski, Amos J. Storkey, Mark E. Bastin
2014	J	`jnl`	The supervised hierarchical Dirichlet process. CoRR Andrew M. Dai, Amos J. Storkey
2013	J	`jnl`	Bayesian Inference in Sparse Gaussian Graphical Models. CoRR Peter Orchard, Felix V. Agakov, Amos J. Storkey
2013	J	`jnl`	Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex? PLoS Comput. Biol. David P. Reichert, Peggy Seriès, Amos J. Storkey
2013	J	`jnl`	Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules CoRR Amos J. Storkey
2013	J	`jnl`	Single subject fMRI test-retest reliability metrics and confounding factors. NeuroImage Krzysztof J. Gorgolewski, Amos J. Storkey, Mark E. Bastin, Ian Whittle, Cyril R. Pernet
2012	A*	`conf`	A Topic Model for Melodic Sequences. ICML Athina Spiliopoulou, Amos J. Storkey
2012	—	`conf`	Continuous Relaxations for Discrete Hamiltonian Monte Carlo. NIPS Yichuan Zhang, Charles Sutton, Amos J. Storkey, Zoubin Ghahramani
2012	A	`conf`	Discriminative Mixtures of Sparse Latent Fields for Risk Management. AISTATS Felix V. Agakov, Peter Orchard, Amos J. Storkey
2012	A*	`conf`	Isoelastic Agents and Wealth Updates in Machine Learning Markets. ICML Amos J. Storkey, Jono Millin, Krzysztof J. Geras
2012	—	`conf`	The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes. NIPS Simon M. J. Lyons, Amos J. Storkey, Simo Särkkä
2011	—	`conf`	A Hierarchical Generative Model of Recurrent Object-Based Attention in the Visual Cortex. ICANN (1) David P. Reichert, Peggy Seriès, Amos J. Storkey
2011	—	`conf`	Comparing Probabilistic Models for Melodic Sequences. ECML/PKDD (3) Athina Spiliopoulou, Amos J. Storkey
2011	J	`jnl`	Machine Learning Markets CoRR Amos J. Storkey
2011	A	`conf`	Machine Learning Markets. AISTATS Amos J. Storkey
2011	—	`conf`	Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability. NIPS David P. Reichert, Peggy Seriès, Amos J. Storkey
2011	J	`jnl`	Particle Smoothing in Continuous Time: A Fast Approach via Density Estimation. IEEE Trans. Signal Process. Lawrence Murray, Amos J. Storkey
2011	—	`conf`	The Grouped Author-Topic Model for Unsupervised Entity Resolution. ICANN (1) Andrew M. Dai, Amos J. Storkey
2010	—	`conf`	Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model. NIPS David P. Reichert, Peggy Seriès, Amos J. Storkey
2010	—	`conf`	Sparse Instrumental Variables (SPIV) for Genome-Wide Studies. NIPS Felix V. Agakov, Paul McKeigue, Jon Krohn, Amos J. Storkey
2009	J	`jnl`	Reproducibility of tract segmentation between sessions using an unsupervised modelling-based approach. NeuroImage Jonathan D. Clayden, Amos J. Storkey, Susana Muñoz Maniega, Mark E. Bastin
2008	J	`jnl`	Tract shape modelling provides evidence of topological change in corpus callosum genu during normal ageing. NeuroImage Mark E. Bastin, Jakub P. Piatkowski, Amos J. Storkey, Laura J. E. Brown, Alasdair M. J. MacLullich, Jonathan D. Clayden
2007	A*	`conf`	A Primitive Based Generative Model to Infer Timing Information in Unpartitioned Handwriting Data. IJCAI Ben H. Williams, Marc Toussaint, Amos J. Storkey
2007	J	`jnl`	A Probabilistic Model-Based Approach to Consistent White Matter Tract Segmentation. IEEE Trans. Medical Imaging Jonathan D. Clayden, Amos J. Storkey, Mark E. Bastin
2007	—	`conf`	Continuous Time Particle Filtering for fMRI. NIPS Lawrence Murray, Amos J. Storkey
2007	—	`conf`	Modelling motion primitives and their timing in biologically executed movements. NIPS Ben H. Williams, Marc Toussaint, Amos J. Storkey
2006	—	`conf`	Extracting Motion Primitives from Natural Handwriting Data. ICANN (2) Ben H. Williams, Marc Toussaint, Amos J. Storkey
2006	J	`jnl`	Improved segmentation reproducibility in group tractography using a quantitative tract similarity measure. NeuroImage Jonathan D. Clayden, Mark E. Bastin, Amos J. Storkey
2006	—	`conf`	Learning Structural Equation Models for fMRI. NIPS Amos J. Storkey, Enrico Simonotto, Heather Whalley, Stephen M. Lawrie, Lawrence Murray, David J. McGonigle
2006	—	`conf`	Mixture Regression for Covariate Shift. NIPS Amos J. Storkey, Masashi Sugiyama
2006	A*	`conf`	Probabilistic inference for solving discrete and continuous state Markov Decision Processes. ICML Marc Toussaint, Amos J. Storkey
2005	—	`conf`	The 2005 PASCAL Visual Object Classes Challenge. MLCW Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang
2004	C	`conf`	Cosine Transform Priors for Enhanced Decoding of Compressed Images. IDEAL Amos J. Storkey, Michael Allan
2003	—	`conf`	Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data. NIPS Amos J. Storkey
2003	J	`jnl`	Image Modeling with Position-Encoding Dynamic Trees. IEEE Trans. Pattern Anal. Mach. Intell. Amos J. Storkey, Christopher K. I. Williams
2003	A	`conf`	Renewal Strings for Cleaning Astronomical Databases. UAI Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann
2002	—	`conf`	Dynamic Structure Super-Resolution. NIPS Amos J. Storkey
2001	A	`conf`	Dynamic Positional Trees for Structural Image Analysis. AISTATS Amos J. Storkey, Christopher K. I. Williams
2000	A	`conf`	Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules. UAI Amos J. Storkey
2000	B	`conf`	MFDTs: Mean Field Dynamic Trees. ICPR Nicholas J. Adams, Amos J. Storkey, Christopher K. I. Williams, Zoubin Ghahramani
1999	J	`jnl`	The basins of attraction of a new Hopfield learning rule. Neural Networks Amos J. Storkey, Romain Valabrègue
1997	C	`conf`	Increasing the Capacity of a Hopfield Network without Sacrificing Functionality. ICANN Amos J. Storkey
1996	C	`conf`	A Modified Spreading Algorithm for Autoassociation in Weightless Neural Networks. ICANN Christopher John Browne, Joel de L. Pereira Castro Jr., Amos J. Storkey