6 January 2011
Tree-Structured Stick Breaking for Hierarchical Data
MCMSki III, Park City, UT

8 December 2010
Tree-Structured Stick Breaking for Hierarchical Data
Advances in Neural Information Processing Systems (NIPS) 24, Vancouver, BC
Online Video

14 August 2010
Monte Carlo Methods for Learning and Inference
CIFAR Neural Computation and Adaptive Perception Summer School, Toronto, ON

9 July 2010
Dependent Probabilistic Matrix Factorization
26th Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA

12 April 2010
Dependent Probabilistic Matrix Factorization
Department of Computer Science, University of Toronto

15 March 2010
Dependent Probabilistic Matrix Factorization
Department of Computer Science, University of Texas at Austin

21 September 2009
Infinite Belief Networks
Department of Computer Science, University of Toronto

18 June 2009
Why Can't Robots See? Lessons From the Human Visual System
IdeaCity 2009

16 June 2009
Archipelago: Nonparametric Bayesian Semi-Supervised Learning
International Conference on Machine Learning, Montreal, Canada
Online video

15 June 2009
Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities
International Conference on Machine Learning, Montreal, Canada
Online video

11 June 2009
Tractable Nonparametric Bayesian Inference in Poisson Processes
Gatsby Computational Neuroscience Unit, University College London

14 May 2009
Tractable Nonparametric Bayesian Inference in Poisson Processes
RAD Lab, University of California at Berkeley

8 April 2009
Tractable Nonparametric Bayesian Inference in Poisson Processes
Machine Learning Department, Carnegie Mellon University

13 March 2009
Tractable Nonparametric Bayesian Inference in Poisson Processes
Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology

17 November 2008
Gaussian Processes for Bayesian Density Modeling
School of Computer Science, University of Manchester

5 August 2008
Practical and Consistent Nonparametric Inference in Gaussian Cox Processes
CIfAR Summer School on Neural Computation and Adaptive Perception (University of Toronto)

24 July 2008
Nonparametric Bayesian Density Modeling with with Gaussian Processes
Machine Learning Group, University of Toronto

16 July 2008
Modeling with Bounded Partition Functions
Cavendish Laboratory, University of Cambridge (Inference Group Meeting)

9 July 2008
Nonparametric Density Modeling with Gaussian Processes
ICML/UAI/COLT Nonparametric Bayes Workshop
Online video

22 April 2008
The Gaussian Process Density Sampler
IST Department, Pennsylvania State University

16 April 2008
The Gaussian Process Density Sampler
Department of Computer Science, Carnegie Mellon University

1 April 2008
The Gaussian Process Density Sampler
Snowbird Learning Workshop

7 March 2008
The Gaussian Process Density Sampler
Department of Computer Science, University of Toronto

30 January 2008
The Gaussian Process Product Model
CIS Department, University of Pennsylvania (MLUNCH)

14 March 2007
Cheap Nonparametric Nonstationarity
Cavendish Laboratory, University of Cambridge (Inference Group Meeting)

14 February 2007
Interesting Things at NIPS
Cavendish Laboratory, University of Cambridge (Inference Group Meeting)

15 November 2006
Vector Function Regression with Gaussian Processes
Cavendish Laboratory, University of Cambridge (Inference Group Meeting)

29 March 2006
Bayesian Online Changepoint Detection
Cavendish Laboratory, University of Cambridge (Inference Group Meeting)

7 June 2005
Scheme: Programming Language of the Gods
Offtopic Lunch, University of Cambridge

14 November 2003
Real-Input Policy Search for Vision and Robotics
Gatsby Computational Neuroscience Unit, University College London

13 November 2003
Real-Input Policy Search for Vision and Robotics
Cavendish Laboratory, University of Cambridge