# Amos J. Storkey

According to our database

Collaborative distances:

^{1}, Amos J. Storkey authored at least 55 papers between 1996 and 2018.Collaborative distances:

## Timeline

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## Bibliography

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

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

Continuously Tempered Hamiltonian Monte Carlo.

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 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.

I. J. Medical Informatics, 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 Processing, 2014

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

NeuroImage, 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 Computational Biology, 2013

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

NeuroImage, 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 Processing, 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. Med. 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

The 2005 PASCAL Visual Object Classes Challenge.

Proceedings of the Machine Learning Challenges, 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