Iain Murray

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George PapamakariosDeepMindAdresse e-mail validée de google.com
Ryan P. AdamsPrinceton UniversityAdresse e-mail validée de princeton.edu
David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeAdresse e-mail validée de mrao.cam.ac.uk
Hugo LarochelleGoogle Brain & MilaAdresse e-mail validée de google.com
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUAdresse e-mail validée de cs.cmu.edu
Benigno UríaGoogle DeepMindAdresse e-mail validée de google.com
Steve RenalsProfessor of Speech Technology, University of EdinburghAdresse e-mail validée de ed.ac.uk
Conor DurkanDeepMindAdresse e-mail validée de deepmind.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresse e-mail validée de eng.cam.ac.uk
Artur BekasovAmazonAdresse e-mail validée de amazon.com
Ben KrauseResearch Scientist, SalesforceAdresse e-mail validée de salesforce.com
Theo PavlakouPhD student, The University of EdinburghAdresse e-mail validée de ed.ac.uk
Mathieu GermainResearcher @ MilaAdresse e-mail validée de usherbrooke.ca
David MimnoAssociate Professor, Cornell UniversityAdresse e-mail validée de cornell.edu
Hanna WallachPartner Research Manager, Microsoft ResearchAdresse e-mail validée de dirichlet.net
Chris WilliamsProfessor of Machine Learning, University of EdinburghAdresse e-mail validée de inf.ed.ac.uk
Asa Cooper SticklandPhD student, University of EdinburghAdresse e-mail validée de ed.ac.uk
Liang LuStaff Speech Scientist, Otter.aiAdresse e-mail validée de ttic.edu
Emmanuel KahembweDoctoral Candidate, The University of Edinburgh, Heriot-Watt University & The Edinburgh Centre forAdresse e-mail validée de ed.ac.uk
George E. DahlGoogle Inc.Adresse e-mail validée de google.com

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Iain Murray

School of Informatics, University of Edinburgh

Adresse e-mail validée de ed.ac.uk - Page d'accueil

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


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Evaluation methods for topic models HM Wallach, I Murray, R Salakhutdinov, D Mimno Proceedings of the 26th annual international conference on machine learning …, 2009	1036	2009
Masked autoregressive flow for density estimation G Papamakarios, T Pavlakou, I Murray Advances in neural information processing systems 30, 2017	743	2017
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	565	2015
The neural autoregressive distribution estimator H Larochelle, I Murray Proceedings of the fourteenth international conference on artificial …, 2011	559	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	513	2008
MCMC for doubly-intractable distributions I Murray, Z Ghahramani, DJC MacKay Proceedings of the 22nd Annual Conference on Uncertainty in Artificial …, 2006	463*	2006
Elliptical slice sampling I Murray, RP Adams, DJC MacKay Journal of Machine Learning Research W&CP 9, 541-548, 2010	434	2010
Neural Spline Flows C Durkan, A Bekasov, I Murray, G Papamakarios arXiv preprint arXiv:1906.04032, 2019	282	2019
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	258	2016
Slice sampling covariance hyperparameters of latent Gaussian models I Murray, RP Adams Advances in neural information processing systems 23, 2010	239	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	239	2009
Fast ε-free inference of simulation models with bayesian conditional density estimation G Papamakarios, I Murray Advances in neural information processing systems 29, 2016	201	2016
RNADE: The real-valued neural autoregressive density-estimator B Uria, I Murray, H Larochelle Advances in Neural Information Processing Systems 26, 2013	200	2013
Multiplicative LSTM for sequence modelling B Krause, L Lu, I Murray, S Renals arXiv preprint arXiv:1609.07959, 2016	178	2016
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	164	2013
Sequential neural likelihood: Fast likelihood-free inference with autoregressive flows G Papamakarios, D Sterratt, I Murray The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	153	2019
A deep and tractable density estimator B Uria, I Murray, H Larochelle Proceedings of The 31st International Conference on Machine Learning, JMLR W …, 2014	151	2014
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	126*	2010
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning AC Stickland, I Murray arXiv preprint arXiv:1902.02671, 2019	124	2019
Advances in Markov chain Monte Carlo methods I Murray University College London, 2007	114	2007

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