Iain Murray

Cited by

	All	Since 2016
Citations	6214	4512
h-index	30	27
i10-index	44	40

1400

700

350

1050

2008200920102011201220132014201520162017201820192020202118 57 71 145 214 259 345 458 566 580 754 978 1342 278

New!

Public access

View all

21 articles

0 articles

available

not available

Based on funding mandates

Co-authors

David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeVerified email at mrao.cam.ac.uk
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
George PapamakariosDeepMindVerified email at google.com
Hugo LarochelleGoogle Brain & MilaVerified email at google.com
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUVerified email at cs.cmu.edu
Benigno UríaGoogle DeepMindVerified email at google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Steve RenalsProfessor of Speech Technology, University of EdinburghVerified email at ed.ac.uk
Ben KrauseResearch Scientist, SalesforceVerified email at salesforce.com
Conor DurkanUniversity of EdinburghVerified email at ed.ac.uk
Theo PavlakouPhD student, The University of EdinburghVerified email at ed.ac.uk
David MimnoAssociate Professor, Cornell UniversityVerified email at cornell.edu
Hanna WallachSenior Principal Researcher, Microsoft ResearchVerified email at dirichlet.net
Artur BekasovUniversity of EdinburghVerified email at ed.ac.uk
Mathieu GermainResearcher @ MilaVerified email at usherbrooke.ca
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Liang LuSenior Applied Scientist, MicrosoftVerified email at microsoft.com
Asa Cooper SticklandPhD student, University of EdinburghVerified email at ed.ac.uk
Emmanuel KahembweDoctoral Candidate, The University of Edinburgh, Heriot-Watt University & The Edinburgh Centre forVerified email at ed.ac.uk
George E. DahlGoogle Inc.Verified email at google.com

Iain Murray

School of Informatics, University of Edinburgh

Verified email at ed.ac.uk - Homepage

Machine Learning Bayesian Inference Hierarchical probabilistic models Markov chain Monte Carlo Density Estimation


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Evaluation methods for topic models HM Wallach, I Murray, R Salakhutdinov, D Mimno Proceedings of the 26th annual international conference on machine learning …, 2009	881	2009
The neural autoregressive distribution estimator H Larochelle, I Murray Proceedings of the Fourteenth International Conference on Artificial …, 2011	489	2011
On the quantitative analysis of deep belief networks R Salakhutdinov, I Murray Proceedings of the 25th international conference on Machine learning, 872-879, 2008	480	2008
Masked autoregressive flow for density estimation G Papamakarios, T Pavlakou, I Murray arXiv preprint arXiv:1705.07057, 2017	436	2017
MCMC for doubly-intractable distributions I Murray, Z Ghahramani, DJC MacKay Proceedings of the 22nd Annual Conference on Uncertainty in Artificial …, 2006	417*	2006
MADE: Masked Autoencoder for Distribution Estimation M Germain, K Gregor, I Murray, H Larochelle Proceedings of the 32nd International Conference on Machine Learning, JMLR W …, 2015	387	2015
Elliptical slice sampling I Murray, RP Adams, DJC MacKay Journal of Machine Learning Research W&CP 9, 541-548, 2010	387	2010
Slice sampling covariance hyperparameters of latent Gaussian models I Murray, RP Adams arXiv preprint arXiv:1006.0868, 2010	220	2010
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities RP Adams, I Murray, DJC MacKay Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	216	2009
Neural autoregressive distribution estimation B Uria, MA Côté, K Gregor, I Murray, H Larochelle The Journal of Machine Learning Research 17 (1), 7184-7220, 2016	184	2016
RNADE: The real-valued neural autoregressive density-estimator B Uria, I Murray, H Larochelle arXiv preprint arXiv:1306.0186, 2013	161	2013
A Framework for Evaluating Approximation Methods for Gaussian Process Regression K Chalupka, CKI Williams, I Murray Journal of Machine Learning Research 14, 333-350, 2013	144	2013
A deep and tractable density estimator B Uria, I Murray, H Larochelle Proceedings of The 31st International Conference on Machine Learning, JMLR W …, 2014	130	2014
Multiplicative LSTM for sequence modelling B Krause, L Lu, I Murray, S Renals arXiv preprint arXiv:1609.07959, 2016	127	2016
Fast -free Inference of Simulation Models with Bayesian Conditional Density Estimation G Papamakarios, I Murray arXiv preprint arXiv:1605.06376, 2016	127	2016
Neural Spline Flows C Durkan, A Bekasov, I Murray, G Papamakarios arXiv preprint arXiv:1906.04032, 2019	111	2019
Incorporating side information into probabilistic matrix factorization using Gaussian processes RP Adams, GE Dahl, I Murray Proceedings of the Twenty-Sixth Conference Annual Conference on Uncertainty …, 2010	109*	2010
Advances in Markov chain Monte Carlo methods I Murray University College London, 2007	109	2007
Bayesian learning in undirected graphical models: approximate MCMC algorithms I Murray, Z Ghahramani arXiv preprint arXiv:1207.4134, 2012	107	2012
Evaluating probabilities under high-dimensional latent variable models I Murray, RR Salakhutdinov Advances in Neural Information Processing Systems 21, 1137-1144, 2009	95	2009

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Upload PDF

Follow this author

Cited by

Co-authors