NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (31)

stat.ML2014

A Deep and Tractable Density Estimator

Benigno Uria, Iain Murray, Hugo Larochelle

cs.LG2016

Neural Autoregressive Distribution Estimation

Benigno Uria, Marc-Alexandre Côté, Karol Gregor +2

stat.CO2012

Driving Markov chain Monte Carlo with a dependent random stream

Iain Murray, Lloyd T. Elliott

stat.CO2009

Nonparametric Bayesian Density Modeling with Gaussian Processes

Ryan Prescott Adams, Iain Murray, David J. C. MacKay

stat.ML2017

Markov Chain Truncation for Doubly-Intractable Inference

Colin Wei, Iain Murray

stat.ML2012

A Framework for Evaluating Approximation Methods for Gaussian Process Regression

Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray

stat.CO2014

Parallel MCMC with Generalized Elliptical Slice Sampling

Robert Nishihara, Iain Murray, Ryan P. Adams

stat.ML2018

Sequential Neural Methods for Likelihood-free Inference

Conor Durkan, George Papamakarios, Iain Murray

stat.CO2010

Slice sampling covariance hyperparameters of latent Gaussian models

Iain Murray, Ryan Prescott Adams

stat.ML2018

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

George Papamakarios, Iain Murray

cs.LG2018

Mode Normalization

Lucas Deecke, Iain Murray, Hakan Bilen

stat.ML2018

Model Criticism in Latent Space

Sohan Seth, Iain Murray, Christopher K. I. Williams

stat.ML2019

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

George Papamakarios, David C. Sterratt, Iain Murray

cs.NE2017

Dynamic Evaluation of Neural Sequence Models

Ben Krause, Emmanuel Kahembwe, Iain Murray +1

stat.ML2018

Masked Autoregressive Flow for Density Estimation

George Papamakarios, Theo Pavlakou, Iain Murray

cs.LG2014

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes

Ryan Prescott Adams, George E. Dahl, Iain Murray

stat.ML2018

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

Artur Bekasov, Iain Murray

cs.LG2012

Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms

Iain Murray, Zoubin Ghahramani

stat.CO2016

Differentiation of the Cholesky decomposition

Iain Murray

stat.CO2016

Pseudo-Marginal Slice Sampling

Iain Murray, Matthew M. Graham

stat.CO2017

A determinant-free method to simulate the parameters of large Gaussian fields

Louis Ellam, Heiko Strathmann, Mark Girolami +1

astro-ph.EP2010

Dynamical inference from a kinematic snapshot: The force law in the Solar System

Jo Bovy, Iain Murray, David W. Hogg

cs.LG2019

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

Asa Cooper Stickland, Iain Murray

stat.ML2014

RNADE: The real-valued neural autoregressive density-estimator

Benigno Uria, Iain Murray, Hugo Larochelle

stat.CO2012

MCMC for doubly-intractable distributions

Iain Murray, Zoubin Ghahramani, David MacKay

stat.CO2010

Elliptical slice sampling

Iain Murray, Ryan Prescott Adams, David J. C. MacKay

cs.LG2019

Dynamic Evaluation of Transformer Language Models

Ben Krause, Emmanuel Kahembwe, Iain Murray +1

cs.NE2017

Multiplicative LSTM for sequence modelling

Ben Krause, Liang Lu, Iain Murray +1

cs.LG2015

MADE: Masked Autoencoder for Distribution Estimation

Mathieu Germain, Karol Gregor, Iain Murray +1

stat.ML2010

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes

Ryan Prescott Adams, George E. Dahl, Iain Murray

stat.ML2019

Cubic-Spline Flows

Conor Durkan, Artur Bekasov, Iain Murray +1