PASCAL Network

Number of records: 33.

	A Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov Processes Christopher Williams Conference or Workshop Item (09 December 2006)
	Advances in Neural Information Processing Systems 22 Book Item not available online. (December 2009)
	An Expectation Maximisation Algorithm for One-to-Many Record Linkage, Illustrated on the Problem of Matching Far Infra-Red Astronomical Sources to Optical Counterparts Amos Storkey, Christopher Williams, Emma Taylor and Robert G Mann Monograph Item not available online. (August 2005)
	Approximate Methods for GP Regression: A Survey and an Empirical Comparison Christopher Williams Conference or Workshop Item (09 June 2005)
	Approximation Methods for Gaussian Process Regression Joaquin Quinonero Candela, Carl Edward Rasmussen and Christopher Williams Book Section Item not available online. (09 November 2006)
	Consistency of Gaussian Process Prediction Christopher Williams Conference or Workshop Item (09 October 2004)
	Dataset issues in object recognition Jean Ponce, T. Berg, Mark Everingham, D. Forsyth, Martial Hebert, S. Lazebnik, Marcin Marszalek, Cordelia Schmid, B. Russell, A. Torralba, Christopher Williams, Jianguo Zhang and Andrew Zisserman Book Section (2006)
	Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care Christopher Williams and John Quinn Conference or Workshop Item (2006)
	Fast Learning of Sprites using Invariant Features Moray Allan, Michalis Titsias and Christopher Williams Conference or Workshop Item (2005)
	Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video Michalis Titsias and Christopher Williams Conference or Workshop Item (02 July 2004)
	Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video Christopher Williams Conference or Workshop Item (08 September 2004)
	Gaussian Processes for Machine Learning Carl Edward Rasmussen and Christopher Williams Book Item not available online. (2006)
	Kernel Multi-task Learning using Task-specific Features Edwin Bonilla, Felix Agakov and Christopher Williams Conference or Workshop Item (March 2007)
	Kernel Multi-task Learning using Task-specific Features. Edwin Bonilla, Felix Agakov and Christopher Williams Conference or Workshop Item (2007)
	Known Unknowns: Novelty Detection in Condition Monitoring John Quinn and Christopher Williams Conference or Workshop Item (June 2007)
	Learning generative texture models with extended Fields-of-Experts Nicolas Heess, Christopher Williams and Geoffrey Hinton Conference or Workshop Item (September 2009)
	Learning Sprites Christopher Williams Conference or Workshop Item (04 May 2004)
	MILEPOST GCC: machine learning based research compiler Grigori Fursin, Cupertino Miranda, Olivier Temam, Mircea Namolaru, Elad Yom-Tov, Ayal Zaks, Bilha Mendelson, Phil Barnard, Elton Ashton, Eric Courtois, Francois Bodin, Edwin Bonilla, John Thomson, Hugh Leather, Christopher Williams and Michael O'Boyle Conference or Workshop Item (June 2008)
	Multi-task Gaussian Process Learning of Robot Inverse Dynamics Kian Ming Chai, Christopher Williams, Stefan Klanke and Sethu Vijayakumar Conference or Workshop Item (2009)
	Multi-task Gaussian process learning of robot inverse dynamics Kian Ming Chai, Christopher Williams, Stefan Klanke and Sethu Vijayakumar Conference or Workshop Item (January 2009)
	Multi-task Gaussian Process Prediction Edwin Bonilla, Kian Ming Chai and Christopher Williams Conference or Workshop Item (2008)
	Object localisation using the Generative Template of Features Moray Allan and Christopher Williams Article (July 2009)
	On a Connection between Object Localization with a Generative Template of Features and Pose-space Prediction Methods Christopher Williams and Moray Allan Other (January 2006)
	On the Eigenspectrum of the Gram Matrix and the Generalisation Error of Kernel PCA John Shawe-Taylor, Christopher Williams, Nello Cristianini and Jaz Kandola Article (2004)
	Predictive Search Distributions Edwin Bonilla, Christopher Williams, Felix Agakov, John Cavazos, John Thompson and Michael F. P. O'Boyle Conference or Workshop Item (June 2006)
	Predictive Search Distributions Edwin Bonilla, Christopher Williams, Felix Agakov, John Cavazos, John Thomson and Michael O'Boyle Conference or Workshop Item (June 2006)
	Signal Masking in Gaussian Channels John A. Quinn and Christopher Williams Conference or Workshop Item (April 2008)
	The 2005 PASCAL Visual Object Classes Challenge Mark Everingham, Andrew Zisserman, Christopher Williams, Luc Van Gool, Moray Allan, Chris Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyorgy Dorko, Stefan Duffner, Jan Eichhorn, Jason Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frederic 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 Storkey, Sandor Szedmak, William Triggs, Ilkay Ulusoy, Ville Viitaniemi and Jianguo Zhang Book Section (2006)
	The PASCAL Visual Object Classes (VOC) challenge Mark Everingham, Luc Van Gool, Christopher Williams, John Winn and Andrew Zisserman Article (September 2009)
	The PASCAL Visual Object Classes Challenge 2006 (VOC 2006) Results Mark Everingham, Andrew Zisserman, Christopher Williams and Luc Van Gool Other (11 September 2006)
	Understanding Gaussian Process Regression Using the Equivalent Kernel Peter Sollich and Christopher Williams Book Section (03 February 2005)
	Using Machine Learning to Focus Iterative Optimization Felix Agakov, Edwin Bonilla, John Cavazos, Bjoern Franke, Grigori Fursin, Michael O'Boyle, John Thomson, Marc Toussaint and Christopher Williams Conference or Workshop Item (March 2006)
	Using the Equivalent Kernel to Understand Gaussian Process Regression Peter Sollich and Christopher Williams Conference or Workshop Item (19 October 2004)

This list was generated on Sat Mar 13 13:31:38 GMT 2010.