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Iain Murray
Iain Murray
School of Informatics, University of Edinburgh and Amazon
Verified email at ed.ac.uk - Homepage
Title
Cited by
Cited by
Year
Masked autoregressive flow for density estimation
G Papamakarios, T Pavlakou, I Murray
Advances in neural information processing systems 30, 2017
12962017
Evaluation methods for topic models
HM Wallach, I Murray, R Salakhutdinov, D Mimno
Proceedings of the 26th annual international conference on machine learning …, 2009
12232009
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
8772015
The neural autoregressive distribution estimator
H Larochelle, I Murray
Proceedings of the fourteenth international conference on artificial …, 2011
6822011
Neural Spline Flows
C Durkan, A Bekasov, I Murray, G Papamakarios
arXiv preprint arXiv:1906.04032, 2019
6392019
On the quantitative analysis of deep belief networks
R Salakhutdinov, I Murray
Proceedings of the 25th international conference on Machine learning, 872-879, 2008
5702008
MCMC for doubly-intractable distributions
I Murray, Z Ghahramani, DJC MacKay
Proceedings of the 22nd Annual Conference on Uncertainty in Artificial …, 2006
532*2006
Elliptical slice sampling
I Murray, RP Adams, DJC MacKay
Journal of Machine Learning Research W&CP 9, 541-548, 2010
5282010
Neural autoregressive distribution estimation
B Uria, MA Côté, K Gregor, I Murray, H Larochelle
Journal of Machine Learning Research 17 (205), 1-37, 2016
3632016
Maximum likelihood training of score-based diffusion models
Y Song, C Durkan, I Murray, S Ermon
Advances in neural information processing systems 34, 1415-1428, 2021
3572021
Fast ε-free inference of simulation models with bayesian conditional density estimation
G Papamakarios, I Murray
Advances in neural information processing systems 29, 2016
3442016
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
2952019
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
2742009
Slice sampling covariance hyperparameters of latent Gaussian models
I Murray, RP Adams
Advances in neural information processing systems 23, 2010
2652010
RNADE: The real-valued neural autoregressive density-estimator
B Uria, I Murray, H Larochelle
Advances in Neural Information Processing Systems 26, 2013
2632013
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
AC Stickland, I Murray
arXiv preprint arXiv:1902.02671, 2019
2612019
Multiplicative LSTM for sequence modelling
B Krause, L Lu, I Murray, S Renals
arXiv preprint arXiv:1609.07959, 2016
2302016
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
2022013
A deep and tractable density estimator
B Uria, I Murray, H Larochelle
Proceedings of The 31st International Conference on Machine Learning, JMLR W …, 2014
1832014
Dynamic evaluation of neural sequence models
B Krause, E Kahembwe, I Murray, S Renals
International Conference on Machine Learning, 2766-2775, 2018
1402018
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