Iain Murray - Google Scholar Citations

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Medförfattare

David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeVerifierad e-postadress på mrao.cam.ac.uk
Ryan P. AdamsPrinceton UniversityVerifierad e-postadress på princeton.edu
Hugo LarochelleGoogle BrainVerifierad e-postadress på usherbrooke.ca
George PapamakariosDeepMindVerifierad e-postadress på google.com
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUVerifierad e-postadress på cs.cmu.edu
Benigno UríaGoogle DeepMindVerifierad e-postadress på google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerifierad e-postadress på eng.cam.ac.uk
Steve RenalsProfessor of Speech Technology, University of EdinburghVerifierad e-postadress på ed.ac.uk
Ben KrauseResearch Scientist, SalesforceVerifierad e-postadress på salesforce.com
David MimnoAssociate Professor, Cornell UniversityVerifierad e-postadress på cornell.edu
Hanna WallachSenior Principal Researcher, Microsoft ResearchVerifierad e-postadress på dirichlet.net
Mathieu GermainResearcher @ MilaVerifierad e-postadress på usherbrooke.ca
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerifierad e-postadress på inf.ed.ac.uk
George E. DahlGoogle BrainVerifierad e-postadress på cs.toronto.edu
peter lathamProfessor, Gatsby Computational Neuroscience Unit, UCLVerifierad e-postadress på gatsby.ucl.ac.uk
Krzysztof ChalupkaCalifornia Institute of TechnologyVerifierad e-postadress på caltech.edu
Robert NishiharaPhD student, UC BerkeleyVerifierad e-postadress på eecs.berkeley.edu
David W HoggNew York University & MPIA & Center for Computational Astrophysics, Flatiron InstituteVerifierad e-postadress på nyu.edu
Jakob MackeComputational Neuroengineering, TU MünchenVerifierad e-postadress på tum.de
Korin RichmondCentre for Speech Technology Research, University of EdinburghVerifierad e-postadress på cstr.ed.ac.uk

Iain Murray

School of Informatics, University of Edinburgh

Verifierad e-postadress på ed.ac.uk - Startsida

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


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Evaluation methods for topic models HM Wallach, I Murray, R Salakhutdinov, D Mimno Proceedings of the 26th annual international conference on machine learning …, 2009	757	2009
On the quantitative analysis of deep belief networks R Salakhutdinov, I Murray Proceedings of the 25th international conference on Machine learning, 872-879, 2008	415	2008
The neural autoregressive distribution estimator H Larochelle, I Murray Proceedings of the Fourteenth International Conference on Artificial …, 2011	390	2011
MCMC for doubly-intractable distributions I Murray, Z Ghahramani, DJC MacKay Proceedings of the 22nd Annual Conference on Uncertainty in Artificial …, 2006	372*	2006
Elliptical slice sampling I Murray, RP Adams, DJC MacKay Journal of Machine Learning Research W&CP 9, 541-548, 2010	339	2010
Masked autoregressive flow for density estimation G Papamakarios, T Pavlakou, I Murray Advances in Neural Information Processing Systems, 2338-2347, 2017	247	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	242	2015
Slice sampling covariance hyperparameters of latent Gaussian models I Murray, RP Adams Advances in neural information processing systems, 1732-1740, 2010	199	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	189	2009
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	123	2013
RNADE: The real-valued neural autoregressive density-estimator B Uria, I Murray, H Larochelle Advances in Neural Information Processing Systems, 2175-2183, 2013	122	2013
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	117	2016
A deep and tractable density estimator B Uria, I Murray, H Larochelle Proceedings of The 31st International Conference on Machine Learning, JMLR W …, 2014	105	2014
Advances in Markov chain Monte Carlo methods I Murray University College London, 2007	103	2007
Bayesian learning in undirected graphical models: approximate MCMC algorithms I Murray, Z Ghahramani Proceedings of the 20th conference on Uncertainty in artificial intelligence …, 2004	101	2004
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	95*	2010
Evaluating probabilities under high-dimensional latent variable models I Murray, RR Salakhutdinov Advances in Neural Information Processing Systems 21, 1137-1144, 2009	92	2009
Fast ε-free inference of simulation models with bayesian conditional density estimation G Papamakarios, I Murray Advances in Neural Information Processing Systems, 1028-1036, 2016	85	2016
Multiplicative LSTM for sequence modelling B Krause, L Lu, I Murray, S Renals arXiv preprint arXiv:1609.07959, 2016	81	2016
The Gaussian process density sampler RP Adams, I Murray, DJC MacKay Advances in Neural Information Processing Systems 21, 9-16, 2009	69*	2009

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