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
9562009
Masked autoregressive flow for density estimation
G Papamakarios, T Pavlakou, I Murray
arXiv preprint arXiv:1705.07057, 2017
5662017
The neural autoregressive distribution estimator
H Larochelle, I Murray
Proceedings of the fourteenth international conference on artificial …, 2011
5252011
On the quantitative analysis of deep belief networks
R Salakhutdinov, I Murray
Proceedings of the 25th international conference on Machine learning, 872-879, 2008
5032008
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
4672015
MCMC for doubly-intractable distributions
I Murray, Z Ghahramani, DJC MacKay
Proceedings of the 22nd Annual Conference on Uncertainty in Artificial …, 2006
444*2006
Elliptical slice sampling
I Murray, RP Adams, DJC MacKay
Journal of Machine Learning Research W&CP 9, 541-548, 2010
4182010
Slice sampling covariance hyperparameters of latent Gaussian models
I Murray, RP Adams
arXiv preprint arXiv:1006.0868, 2010
2302010
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
2292009
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
2272016
RNADE: The real-valued neural autoregressive density-estimator
B Uria, I Murray, H Larochelle
arXiv preprint arXiv:1306.0186, 2013
1832013
Neural Spline Flows
C Durkan, A Bekasov, I Murray, G Papamakarios
arXiv preprint arXiv:1906.04032, 2019
1562019
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
1552016
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
1522013
Multiplicative LSTM for sequence modelling
B Krause, L Lu, I Murray, S Renals
arXiv preprint arXiv:1609.07959, 2016
1442016
A deep and tractable density estimator
B Uria, I Murray, H Larochelle
Proceedings of The 31st International Conference on Machine Learning, JMLR W …, 2014
1362014
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
118*2010
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
1112019
Advances in Markov chain Monte Carlo methods
I Murray
University College London, 2007
1112007
Bayesian learning in undirected graphical models: approximate MCMC algorithms
I Murray, Z Ghahramani
arXiv preprint arXiv:1207.4134, 2012
1102012
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Articles 1–20