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Density Deconvolution with Normalizing Flows

Jul 13, 2020
Tim Dockhorn, James A. Ritchie, Yaoliang Yu, Iain Murray

* Appearing at the second workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (ICML 2020), Virtual Conference. 8 pages, 6 figures, 5 tables 

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Diverse Ensembles Improve Calibration

Jul 08, 2020
Asa Cooper Stickland, Iain Murray

* Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning 

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Ordering Dimensions with Nested Dropout Normalizing Flows

Jun 15, 2020
Artur Bekasov, Iain Murray


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On Contrastive Learning for Likelihood-free Inference

Feb 10, 2020
Conor Durkan, Iain Murray, George Papamakarios


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Scalable Extreme Deconvolution

Nov 26, 2019
James A. Ritchie, Iain Murray

* Appearing at the Second Workshop on Machine Learning and the Physical Sciences (NeurIPS 2019), Vancouver, Canada 

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CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting

Jul 29, 2019
Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras


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Neural Spline Flows

Jun 10, 2019
Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios


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Cubic-Spline Flows

Jun 05, 2019
Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios

* Appeared at the 1st Workshop on Invertible Neural Networks and Normalizing Flows at ICML 2019 

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Dynamic Evaluation of Transformer Language Models

Apr 17, 2019
Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals


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BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning

Feb 07, 2019
Asa Cooper Stickland, Iain Murray


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Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting

Nov 29, 2018
Artur Bekasov, Iain Murray

* To appear in the third workshop on Bayesian Deep Learning (NeurIPS 2018), Montreal, Canada 

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Sequential Neural Methods for Likelihood-free Inference

Nov 21, 2018
Conor Durkan, George Papamakarios, Iain Murray


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Mode Normalization

Oct 12, 2018
Lucas Deecke, Iain Murray, Hakan Bilen


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Model Criticism in Latent Space

Jul 02, 2018
Sohan Seth, Iain Murray, Christopher K. I. Williams


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Masked Autoregressive Flow for Density Estimation

Jun 14, 2018
George Papamakarios, Theo Pavlakou, Iain Murray

* section 4.3 is corrected since the previous version 

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Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows

May 18, 2018
George Papamakarios, David C. Sterratt, Iain Murray


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Fast $ε$-free Inference of Simulation Models with Bayesian Conditional Density Estimation

Apr 02, 2018
George Papamakarios, Iain Murray

* Appeared at NIPS 2016. Fixed typo in Eq (37) 

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Dynamic Evaluation of Neural Sequence Models

Oct 25, 2017
Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals


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Multiplicative LSTM for sequence modelling

Oct 12, 2017
Ben Krause, Liang Lu, Iain Murray, Steve Renals


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Markov Chain Truncation for Doubly-Intractable Inference

Mar 11, 2017
Colin Wei, Iain Murray


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Neural Autoregressive Distribution Estimation

May 27, 2016
Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle


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MADE: Masked Autoencoder for Distribution Estimation

Jun 05, 2015
Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle

* Proceedings of the 32nd International Conference on Machine Learning, JMLR W&CP 37:881-889, 2015 
* 9 pages and 1 page of supplementary material. Updated to match published version 

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Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes

Aug 09, 2014
Ryan Prescott Adams, George E. Dahl, Iain Murray

* Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010) 

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Parallel MCMC with Generalized Elliptical Slice Sampling

Jul 24, 2014
Robert Nishihara, Iain Murray, Ryan P. Adams

* Journal of Machine Learning Research 15:2087-2112, 2014 
* 19 pages, 8 figures, 3 algorithms 

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A Deep and Tractable Density Estimator

Jan 11, 2014
Benigno Uria, Iain Murray, Hugo Larochelle

* 9 pages, 4 tables, 1 algorithm, 5 figures. To appear ICML 2014, JMLR W&CP volume 32 

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RNADE: The real-valued neural autoregressive density-estimator

Jan 09, 2014
Benigno Uria, Iain Murray, Hugo Larochelle

* Advances in Neural Information Processing Systems 26:2175-2183, 2013 
* 12 pages, 3 figures, 3 tables, 2 algorithms. Merges the published paper and supplementary material into one document 

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A Framework for Evaluating Approximation Methods for Gaussian Process Regression

Nov 05, 2012
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray

* 19 pages, 4 figures 

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Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms

Jul 11, 2012
Iain Murray, Zoubin Ghahramani

* Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004) 

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Slice sampling covariance hyperparameters of latent Gaussian models

Oct 28, 2010
Iain Murray, Ryan Prescott Adams

* 9 pages, 4 figures, 4 algorithms. Minor corrections to previous version. This version to appear in Advances in Neural Information Processing Systems (NIPS) 23, 2010 

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