Iain Murray
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
9122009
The neural autoregressive distribution estimator
H Larochelle, I Murray
Proceedings of the Fourteenth International Conference on Artificial …, 2011
5022011
On the quantitative analysis of deep belief networks
R Salakhutdinov, I Murray
Proceedings of the 25th international conference on Machine learning, 872-879, 2008
4902008
Masked autoregressive flow for density estimation
G Papamakarios, T Pavlakou, I Murray
arXiv preprint arXiv:1705.07057, 2017
4812017
MCMC for doubly-intractable distributions
I Murray, Z Ghahramani, DJC MacKay
Proceedings of the 22nd Annual Conference on Uncertainty in Artificial …, 2006
428*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
4202015
Elliptical slice sampling
I Murray, RP Adams, DJC MacKay
Journal of Machine Learning Research W&CP 9, 541-548, 2010
4032010
Slice sampling covariance hyperparameters of latent Gaussian models
I Murray, RP Adams
arXiv preprint arXiv:1006.0868, 2010
2252010
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
2222009
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
1972016
RNADE: The real-valued neural autoregressive density-estimator
B Uria, I Murray, H Larochelle
arXiv preprint arXiv:1306.0186, 2013
1702013
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
1452013
Fast -free Inference of Simulation Models with Bayesian Conditional Density Estimation
G Papamakarios, I Murray
arXiv preprint arXiv:1605.06376, 2016
1362016
Multiplicative LSTM for sequence modelling
B Krause, L Lu, I Murray, S Renals
arXiv preprint arXiv:1609.07959, 2016
1342016
A deep and tractable density estimator
B Uria, I Murray, H Larochelle
Proceedings of The 31st International Conference on Machine Learning, JMLR W …, 2014
1332014
Neural Spline Flows
C Durkan, A Bekasov, I Murray, G Papamakarios
arXiv preprint arXiv:1906.04032, 2019
1322019
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
112*2010
Advances in Markov chain Monte Carlo methods
I Murray
University College London, 2007
1102007
Bayesian learning in undirected graphical models: approximate MCMC algorithms
I Murray, Z Ghahramani
arXiv preprint arXiv:1207.4134, 2012
1072012
Evaluating probabilities under high-dimensional latent variable models
I Murray, RR Salakhutdinov
Advances in Neural Information Processing Systems 21, 1137-1144, 2009
972009
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Articles 1–20