Publications by Iain Murray

I have a separate page on how to view PDF and DjVu files. If you like having the GoogleViewer links, see this script.

Refereed publications

• How biased are maximum entropy models?
  Jakob H. Macke, Iain Murray, and Peter E. Latham.
  Advances in Neural Information Processing Systems 24, 2011. [Abstract, PDF, DjVu, GoogleViewer, BibTeX]
• The Neural Autoregressive Distribution Estimator.
  Hugo Larochelle and Iain Murray.
  JMLR W&CP 15:29–37, 2011.
  [Abstract and code, PDF, DjVu, GoogleViewer, BibTeX, Discussion]
  Notable paper award.
• Slice sampling covariance hyperparameters of latent Gaussian models
  Iain Murray and Ryan Prescott Adams.
  Advances in Neural Information Processing Systems 23, 2010. [Abstract and code, PDF, DjVu, GoogleViewer, arXiv, Related Poster, BibTeX, VideoLecture]
• Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
  Ryan Prescott Adams, George E. Dahl and Iain Murray.
  Proceedings of the 26th Annual Conference on Uncertainty in Artificial Intelligence (UAI), 2010.
  [Abstract and code, PDF, DjVu, GoogleViewer, arXiv, BibTeX]
• Elliptical slice sampling.
  Iain Murray, Ryan Prescott Adams and David J.C. MacKay.
  JMLR W&CP 9:541–548, 2010.
  [Abstract and code, PDF, DjVu, GoogleViewer, arXiv, Poster, BibTeX]
• Dynamical inference from a kinematic snapshot: the force law in the solar system.
  Jo Bovy, Iain Murray and David W. Hogg.
  ApJ 711(2):1157–1167, 2010.
  [ApJ, arXiv/0903.5308, BibTeX].
• 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 and code, 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]
• Characterizing response behavior in multisensory perception with conflicting cues.
  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, Code]
• 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]

Workshop presentations

This list is incomplete.

• Gaussian Processes and Fast Matrix-Vector Multiplies.
  Iain Murray
  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.
• 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

Some of my work is available as preprints on arXiv.

• Driving Markov chain Monte Carlo with a dependent random stream.
  Iain Murray and Lloyd T. Elliott.
  [arXiv/1204.3187].
• Nonparametric Bayesian Density Modeling with Gaussian Processes.
  Ryan Prescott Adams, Iain Murray and David J.C. MacKay.
  Submitted, 2009. [arXiv/0912.4896].

Contributed discussions

• Discussion on the paper: Catching up faster by switching sooner…, by Erven, Grünwald and Rooij
  Iain Murray.
  Journal of the Royal Statistical Society: Series B (Statistical Methodology), to appear, 2012. [PDF, DjVu, GoogleViewer]
• Discussion on the paper: Riemann manifold Langevin and Hamiltonian Monte Carlo methods, by Girolami and Calderhead
  Iain Murray and Ryan Prescott Adams.
  Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(2):191–192, 2011. [Full paper, PDF, DjVu, GoogleViewer]
• Using TPA for Bayesian inference — Discussion
  Iain Murray.
  Bayesian Statistics 9, pp. 273–275, Oxford University Press, 2011. [PDF, DjVu, GoogleViewer]

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]

Notes and Technical Reports

• Smooth histograms from MCMC. Iain Murray, 2011.
  [HTML note]
• 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