Iain Murray’s Publications

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Refereed conference publications

• Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities.
  Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
  Proceedings of the 26th International Conference on Machine Learning (ICML), 2009. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
  
  ICML Best Student Paper Honourable Mention
• Evaluation Methods for Topic Models. Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov and David Mimno.
  Proceedings of the 26th International Conference on Machine Learning (ICML), 2009. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
• Evaluating probabilities under high-dimensional latent variable models.
  Iain Murray and Ruslan Salakhutdinov.
  Advances in Neural Information Processing Systems 21, 2009. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
• The Gaussian Process Density Sampler.
  Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
  Advances in Neural Information Processing Systems 21, 2009. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
• 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, 2009. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
• On the Quantitative Analysis of Deep Belief Networks.
  Ruslan Salakhutdinov and Iain Murray.
  Proceedings of the 25th International Conference on Machine Learning (ICML), 2008. [Abstract, PDF, DjVu, GoogleViewer, BibTeX].
• 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. [Abstract, PDF, DjVu, GoogleViewer, BibTeX].
• Nested sampling for Potts Models.
  Iain Murray, David J.C. MacKay, Zoubin Ghahramani,
  John Skilling. Advances in Neural Information Processing Systems 18, 2006. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
• 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. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]

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. Springer Lecture Notes in Computer Science. 2006.
  [Abstract and PDF free from Springer, GoogleViewer, BibTeX]

Pre-prints

I am intending to put more of my preprints on arXiv in future.

• Elliptical slice sampling.
  Iain Murray, Ryan Prescott Adams and David J.C. MacKay. Submitted, 2009. [arXiv/1001.0175].
• Nonparametric Bayesian Density Modeling with Gaussian Processes. Ryan Prescott Adams, Iain Murray and David J.C. MacKay. Submitted, 2009. [arXiv/0912.4896].
• The gravitational force law in the Solar System.
  Jo Bovy, Iain Murray and David W. Hogg. Submitted to ApJ, 2009. [arXiv/0903.5308].

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 honorable mention for the Savage award.

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

Unrefereed conference or workshop presentations

This list is incomplete.

• Gaussian Processes and Fast Matrix-Vector Multiplies. Iain Murray, 2009. Presented at the Numerical Mathematics in Machine Learning workshop at the 26th International Conference on Machine Learning (ICML 2009), Montreal, Canada. [Abstract, PDF, DjVu, GoogleViewer, BibTeX].
  
  The talk, available online, covered slightly different material.

Notes and Technical Reports

• Notes on unknown uniform distributions in hierarchical probabilistic models. Iain Murray, 2009. [Abstract, PDF, DjVu, GoogleViewer, BibTeX].
• Notes on the KL-divergence between a Markov chain and its equilibrium distribution.
  Iain Murray and Ruslan Salakhutdinov, 2008.
  [Abstract, PDF, DjVu, GoogleViewer, BibTeX].
• 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, GoogleViewer, BibTeX].
• Note on Rejection sampling and exact sampling with the Metropolised Independence Sampler.
  Iain Murray, 2004. [Abstract, PDF, DjVu, GoogleViewer, BibTeX].

See also materials on my teaching page.

My Erdős number is 3 through:
David J.C. MacKay → Robert James McEliece → Paul Erdős.

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Iain Murray.