Iain Murray

According to our database1, Iain Murray authored at least 53 papers between 2004 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2019
Dynamic Evaluation of Transformer Language Models.
CoRR, 2019

BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning.
CoRR, 2019

2018
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting.
CoRR, 2018

Sequential Neural Methods for Likelihood-free Inference.
CoRR, 2018

Mode Normalization.
CoRR, 2018

Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows.
CoRR, 2018

Dynamic Evaluation of Neural Sequence Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Dynamic Evaluation of Neural Sequence Models.
CoRR, 2017

Masked Autoregressive Flow for Density Estimation.
CoRR, 2017

Masked Autoregressive Flow for Density Estimation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multiplicative LSTM for sequence modelling.
Proceedings of the 5th International Conference on Learning Representations, 2017

Aye or naw, whit dae ye hink? Scottish independence and linguistic identity on social media.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

Markov Chain Truncation for Doubly-Intractable Inference.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Neural Autoregressive Distribution Estimation.
Journal of Machine Learning Research, 2016

Markov Chain Truncation for Doubly-Intractable Inference.
CoRR, 2016

Neural Autoregressive Distribution Estimation.
CoRR, 2016

Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation.
CoRR, 2016

Differentiation of the Cholesky decomposition.
CoRR, 2016

Multiplicative LSTM for sequence modelling.
CoRR, 2016

Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Pseudo-Marginal Slice Sampling.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
MADE: Masked Autoencoder for Distribution Estimation.
CoRR, 2015

MADE: Masked Autoencoder for Distribution Estimation.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Modelling acoustic feature dependencies with artificial neural networks: Trajectory-RNADE.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Parallel MCMC with generalized elliptical slice sampling.
Journal of Machine Learning Research, 2014

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes.
CoRR, 2014

A Deep and Tractable Density Estimator.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Attention as Reward-Driven Optimization of Sensory Processing.
Neural Computation, 2013

A framework for evaluating approximation methods for Gaussian process regression.
Journal of Machine Learning Research, 2013

Estimation Bias in Maximum Entropy Models.
Entropy, 2013

A Deep and Tractable Density Estimator.
CoRR, 2013

NADE: The real-valued neural autoregressive density-estimator.
CoRR, 2013

RNADE: The real-valued neural autoregressive density-estimator.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

A Composable Strategy for Shredded Document Reconstruction.
Proceedings of the Computer Analysis of Images and Patterns, 2013

2012
Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms
CoRR, 2012

A Framework for Evaluating Approximation Methods for Gaussian Process Regression
CoRR, 2012

Deep Architectures for Articulatory Inversion.
Proceedings of the INTERSPEECH 2012, 2012

2011
The Neural Autoregressive Distribution Estimator.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

How biased are maximum entropy models?
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Elliptical slice sampling.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
CoRR, 2010

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes.
Proceedings of the UAI 2010, 2010

Slice sampling covariance hyperparameters of latent Gaussian models.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Evaluation methods for topic models.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Characterizing response behavior in multisensory perception with conflicting cues.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Evaluating probabilities under high-dimensional latent variable models.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

The Gaussian Process Density Sampler.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

On the quantitative analysis of deep belief networks.
Proceedings of the Machine Learning, 2008

2006
MCMC for Doubly-intractable Distributions.
Proceedings of the UAI '06, 2006

2005
Nested sampling for Potts models.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

A Pragmatic Bayesian Approach to Predictive Uncertainty.
Proceedings of the Machine Learning Challenges, 2005

2004
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms.
Proceedings of the UAI '04, 2004


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