Iain Murray’s Publications

I have a separate page on how to view PDF and DjVu files.

Refereed conference publications

• Evaluating probabilities under high-dimensional latent variable models. Iain Murray and Ruslan Salakhutdinov. Advances in Neural Information Processing Systems 21, (to appear 2009).
• The Gaussian Process Density Sampler. Ryan P. Adams, Iain Murray and David J.C. MacKay. Advances in Neural Information Processing Systems 21, (to appear 2009).
• Comparing model predictions of response bias and variance in cue combination. Rama Natarajan, Iain Murray, Ladan Shams and Richard Zemel. Advances in Neural Information Processing Systems 21, (to appear 2009).
• On the Quantitative Analysis of Deep Belief Networks.
  Ruslan Salakhutdinov and Iain Murray.
  Proceedings of the 25th International Conference on Machine Learning (ICML), 2008. [PDF, DjVu, JavaDjVu].
• MCMC for doubly-intractable distributions.
  Iain Murray, Zoubin Ghahramani, David J.C. MacKay.
  Proceedings of the 22nd Annual Conference on Uncertainty in Artificial Intelligence (UAI), 2006. [PDF, DjVu, JavaDjVu].
• Nested sampling for Potts Models. Iain Murray, David J.C. MacKay, Zoubin Ghahramani, John Skilling. Advances in Neural Information Processing Systems 18, 2006. [PDF, DjVu, JavaDjVu]
• Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms. Iain Murray and Zoubin Ghahramani. Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI), 2004. [PDF, DjVu, JavaDjVu]

PhD thesis

My thesis contains more work on nested sampling, doubly-intractable distributions and Markov chain Monte Carlo (MCMC) in general than in my earlier publications. The thesis received an honourable mention for the Savage award.

Advances in Markov chain Monte Carlo methods, Iain Murray, PhD thesis, Gatsby computational neuroscience unit, University College London, 2007. [PDF, DjVu, JavaDjVu].

Book chapter (refereed workshop proceedings)

• A pragmatic Bayesian approach to predictive uncertainty. Iain Murray and Edward Snelson. Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Textual Entailment.: First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11–13, 2005, Revised Selected Papers. Joaquin Quiñonero-Candela, Ido Dagan, Bernardo Magnini and Florence D’Alché-Buc (Eds). Springer Lecture Notes in Computer Science. 2006.

Notes and Technical Reports

• Notes on the KL-divergence between a Markov chain and its equilibrium distribution. Iain Murray and Ruslan Salakhutdinov 2008. [PDF, DjVu, JavaDjVu].
• A note on the evidence and Bayesian Occam’s razor. Iain Murray and Zoubin Ghahramani. Gatsby Unit Technical Report GCNU-TR 2005-003. August 2005. [Abstract, PDF, DjVu, JavaDjVu].
• Note on Rejection sampling and exact sampling with the Metropolised Independence Sampler. Iain Murray. 2004. [Abstract, PDF, DjVu, JavaDjVu].

See also materials on my teaching page.

---

Iain Murray.