Christopher K. I. Williams

According to our database1, Christopher K. I. Williams authored at least 104 papers between 1991 and 2018.

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Bibliography

2018
Estimating Bacterial and Cellular Load in FCFM Imaging.
J. Imaging, 2018

Inverting Supervised Representations with Autoregressive Neural Density Models.
CoRR, 2018

Autoencoders and Probabilistic Inference with Missing Data: An Exact Solution for The Factor Analysis Case.
CoRR, 2018

2017
The shape variational autoencoder: A deep generative model of part-segmented 3D objects.
Comput. Graph. Forum, 2017

Estimating Bacterial Load in FCFM Imaging.
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017

Vision-as-Inverse-Graphics: Obtaining a Rich 3D Explanation of a Scene from a Single Image.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016
Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers.
CoRR, 2016

Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring.
CoRR, 2016

Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring.
Proceedings of the 1st Machine Learning in Health Care, 2016

Overcoming Occlusion with Inverse Graphics.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

2015
The Pascal Visual Object Classes Challenge: A Retrospective.
International Journal of Computer Vision, 2015

Tree-Cut for Probabilistic Image Segmentation.
CoRR, 2015

Discriminative Switching Linear Dynamical Systems applied to Physiological Condition Monitoring.
CoRR, 2015

Discriminative Switching Linear Dynamical Systems applied to Physiological Condition Monitoring.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

2014
Autoregressive Hidden Markov Models for the Early Detection of Neonatal Sepsis.
IEEE J. Biomedical and Health Informatics, 2014

The Shape Boltzmann Machine: A Strong Model of Object Shape.
International Journal of Computer Vision, 2014

Renewal Strings for Cleaning Astronomical Databases.
CoRR, 2014

A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
A framework for evaluating approximation methods for Gaussian process regression.
Journal of Machine Learning Research, 2013

Dictionary of Computer Vision and Image Processing, Second Edition.
Wiley, ISBN: 978-1-119-94186-6, 2013

2012
In Memoriam: Mark Everingham.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Multiple Texture Boltzmann Machines.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

A Framework for Evaluating Approximation Methods for Gaussian Process Regression
CoRR, 2012

A Generative Model for Parts-based Object Segmentation.
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

2011
Greedy Learning of Binary Latent Trees.
IEEE Trans. Pattern Anal. Mach. Intell., 2011

Milepost GCC: Machine Learning Enabled Self-tuning Compiler.
International Journal of Parallel Programming, 2011

Special Issue on Probabilistic Models for Image Understanding, Part II.
International Journal of Computer Vision, 2011

Transformation Equivariant Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Automating the Calibration of a Neonatal Condition Monitoring System.
Proceedings of the Artificial Intelligence in Medicine, 2011

2010
Editorial: Special Issue on Probabilistic Models for Image Understanding.
International Journal of Computer Vision, 2010

The Pascal Visual Object Classes (VOC) Challenge.
International Journal of Computer Vision, 2010

2009
Factorial Switching Linear Dynamical Systems Applied to Physiological Condition Monitoring.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Object localisation using the Generative Template of Features.
Computer Vision and Image Understanding, 2009

Learning Generative Texture Models with extended Fields-of-Experts.
Proceedings of the British Machine Vision Conference, 2009

2008
Multi-task Gaussian Process Learning of Robot Inverse Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Signal masking in Gaussian channels.
Proceedings of the IEEE International Conference on Acoustics, 2008

2007
Kernel Multi-task Learning using Task-specific Features.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Multi-task Gaussian Process Prediction.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Known Unknowns: Novelty Detection in Condition Monitoring.
Proceedings of the Pattern Recognition and Image Analysis, Third Iberian Conference, 2007

2006
A regularized discriminative model for the prediction of protein-peptide interactions.
Bioinformatics, 2006

Predictive search distributions.
Proceedings of the Machine Learning, 2006

Sequential Learning of Layered Models from Video.
Proceedings of the Toward Category-Level Object Recognition, 2006


Using Machine Learning to Focus Iterative Optimization.
Proceedings of the Fourth IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2006), 2006

Gaussian processes for machine learning.
Adaptive computation and machine learning, MIT Press, ISBN: 026218253X, 2006

2005
On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA.
IEEE Trans. Information Theory, 2005

How to Pretend That Correlated Variables Are Independent by Using Difference Observations.
Neural Computation, 2005

Probabilistic in Silico Prediction of Protein-Peptide Interactions.
Proceedings of the Systems Biology and Regulatory Genomics, 2005

Unsupervised Learning of Multiple Aspects of Moving Objects from Video.
Proceedings of the Advances in Informatics, 2005

Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005


Fast Learning of Sprites using Invariant Features.
Proceedings of the British Machine Vision Conference 2005, Oxford, UK, September 2005, 2005

2004
Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning.
Neural Computation, 2004

Using the Equivalent Kernel to Understand Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Harmonising Chorales by Probabilistic Inference.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Understanding Gaussian Process Regression Using the Equivalent Kernel.
Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2004

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

Dynamic trees for image modelling.
Image Vision Comput., 2003

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

On the Number of Modes of a Gaussian Mixture.
Proceedings of the Scale Space Methods in Computer Vision, 4th International Conference, 2003

Extreme Components Analysis.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Fast Forward Selection to Speed Up Sparse Gaussian Process Regression.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002
Combining Belief Networks and Neural Networks for Scene Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Products of Gaussians and Probabilistic Minor Component Analysis.
Neural Computation, 2002

On a Connection between Kernel PCA and Metric Multidimensional Scaling.
Machine Learning, 2002

Learning About Multiple Objects in Images: Factorial Learning without Factorial Search.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Dynamic Trees: Learning to Model Outdoor Scenes.
Proceedings of the Computer Vision, 2002

On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum.
Proceedings of the Discovery Science, 5th International Conference, 2002

On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum.
Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2001
Comparing Bayesian neural network algorithms for classifying segmented outdoor images.
Neural Networks, 2001

Products of Gaussians.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

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

2000
Upper and Lower Bounds on the Learning Curve for Gaussian Processes.
Machine Learning, 2000

Bayesian inference for wind field retrieval.
Neurocomputing, 2000

Using the Nyström Method to Speed Up Kernel Machines.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

On a Connection between Kernel PCA and Metric Multidimensional Scaling.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

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

The Effect of the Input Density Distribution on Kernel-based Classifiers.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999
A MCMC Approach to Hierarchical Mixture Modelling.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998
Bayesian Classification With Gaussian Processes.
IEEE Trans. Pattern Anal. Mach. Intell., 1998

Computation with Infinite Neural Networks.
Neural Computation, 1998

GTM: The Generative Topographic Mapping.
Neural Computation, 1998

Developments of the generative topographic mapping.
Neurocomputing, 1998

DTs: Dynamic Trees.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Discovering Hidden Features with Gaussian Processes Regression.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Finite-Dimensional Approximation of Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

1997
Instantiating Deformable Models with a Neural Net.
Computer Vision and Image Understanding, 1997

Regression with Input-dependent Noise: A Gaussian Process Treatment.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1996
Using Generative Models for Handwritten Digit Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., 1996

Computing with Infinite Networks.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

GTM: A Principled Alternative to the Self-Organizing Map.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

GTM: A Principled Alternative to the Self-Organizing Map.
Proceedings of the Artificial Neural Networks, 1996

1995
Lending direction to neural networks.
Neural Networks, 1995

Gaussian Processes for Regression.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

EM Optimization of Latent-Variables Density Models.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994
Using a neural net to instantiate a deformable model.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1992
Learning to Segment Images Using Dynamic Feature Binding.
Neural Computation, 1992

Directional-Unit Boltzmann Machines.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991
Adaptive Elastic Models for Hand-Printed Character Recognition.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991


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