Refereed Conference Papers

Ryan Prescott Adams and Zoubin Ghahramani.
Archipelago: Nonparametric Bayesian Semi-Supervised Learning.
In Proceedings of the 26th International Conference on Machine Learning (ICML 2009). 2009.
Honourable Mention for ICML Best Paper
abstract | pdf | ps | bibtex
Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities.
In Proceedings of the 26th International Conference on Machine Learning (ICML 2009). 2009.
Honourable Mention for ICML Best Student Paper
abstract | pdf | ps | bibtex
Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
The Gaussian Process Density Sampler.
In Advances in Neural Information Processing Systems 21 (NIPS 2008). 2009.
abstract | pdf | ps | bibtex
Ryan Prescott Adams and Oliver Stegle.
Gaussian Process Product Models for Nonparametric Nonstationarity.
In Proceedings of the 25th International Conference on Machine Learning (ICML-2008). 2008.
abstract | pdf | ps | bibtex

Refereed Abstracts

Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
Nonparametric Bayesian Density Modeling with Gaussian Processes.
ICML/UAI Nonparametric Bayes Workshop. 2008.
pdf | ps
Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
The Gaussian process density sampler.
Snowbird Learning Workshop (Talk). 2008.
pdf | ps

Technical Reports

Ryan Prescott Adams and David J.C. MacKay.
Bayesian online changepoint detection.
University of Cambridge Technical Report. arXiv:0710.3742v1 [stat.ML]. 2007.
abstract | pdf | ps | bibtex

Working Papers

Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
Nonparametric Bayesian Density Estimation with Gaussian Processes.
pdf

Theses

Ryan Prescott Adams
Kernel Methods for Nonparametric Bayesian Inference of Probabilities and Point Processes.
PhD Thesis, Department of Physics, University of Cambridge. 2009.
abstract | pdf | ps | bibtex