Iain Murray

发表

On the quantitative analysis of deep belief networks

Ruslan Salakhutdinov, Iain Murray, R. Salakhutdinov, 2008, ICML '08.

Evaluating probabilities under high-dimensional latent variable models

Ruslan Salakhutdinov, Iain Murray, R. Salakhutdinov, 2008, NIPS.

Introduction To Gaussian Processes

Iain Murray, 2008 .

The Neural Autoregressive Distribution Estimator

Iain Murray, H. Larochelle, 2011, AISTATS.

Masked Autoregressive Flow for Density Estimation

Iain Murray, George Papamakarios, Theo Pavlakou, 2017, NIPS.

Notes on the KL-divergence between a Markov chain and its equilibrium distribution

R. Salakhutdinov, Iain Murray, 2008 .

The Neural Autoregressive Distribution Estimator

Hugo Larochelle, Iain Murray, Iain Murray, 2011, AISTATS.

Gaussian Processes and Fast Matrix-Vector Multiplies

Iain Murray, 2009 .

RNADE: The real-valued neural autoregressive density-estimator

Hugo Larochelle, Iain Murray, Benigno Uria, 2013, NIPS.

MCMC for Doubly-intractable Distributions

Zoubin Ghahramani, Iain Murray, David J. C. MacKay, 2006, UAI.

Modelling acoustic feature dependencies with artificial neural networks: Trajectory-RNADE

Cassia Valentini-Botinhao, Steve Renals, Benigno Uria, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Neural Autoregressive Distribution Estimation

Hugo Larochelle, Iain Murray, Benigno Uria, 2016, J. Mach. Learn. Res..

Parallel MCMC with generalized elliptical slice sampling

Ryan P. Adams, Iain Murray, Robert Nishihara, 2012, J. Mach. Learn. Res..

Neural Spline Flows

Iain Murray, George Papamakarios, Conor Durkan, 2019, NeurIPS.

Slice sampling covariance hyperparameters of latent Gaussian models

Ryan P. Adams, Iain Murray, Iain Murray, 2010, NIPS.

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

Iain Murray, George Papamakarios, Iain Murray, 2016, 1605.06376.

Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010)

Ryan P. Adams, Iain Murray, George E. Dahl, 2010 .

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes pdf

Ryan P. Adams, Iain Murray, George E. Dahl, 2010, UAI.

Multiplicative LSTM for sequence modelling pdf

Steve Renals, Liang Lu, Ben Krause, 2016, ICLR.

A framework for evaluating approximation methods for Gaussian process regression

Iain Murray, Christopher K. I. Williams, Krzysztof Chalupka, 2012, J. Mach. Learn. Res..

Elliptical slice sampling

Ryan P. Adams, Iain Murray, David J. C. MacKay, 2009, AISTATS.

Model Criticism in Latent Space

Christopher K. I. Williams, Iain Murray, Sohan Seth, 2017, Bayesian Analysis.

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

Iain Murray, Asa Cooper Stickland, Iain Murray, 2019, ICML.

A Composable Strategy for Shredded Document Reconstruction

Iain Murray, Razvan Ranca, Iain Murray, 2013, CAIP.

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

Iain Murray, Mark Girolami, Louis Ellam, 2017, 1709.03312.

Evaluation methods for topic models

Ruslan Salakhutdinov, Iain Murray, Hanna M. Wallach, 2009, ICML '09.

Introduction to Gaussian Processes

Iain Murray, Iain Murray, Iain Murray, 2008 .

A Deep and Tractable Density Estimator

Hugo Larochelle, Iain Murray, Benigno Uria, 2013, ICML.

Gaussian Processes and Fast Matrix-Vector Multiplies

Iain Murray, 2009 .

Driving Markov chain Monte Carlo with a dependent random stream

Lloyd T. Elliott, Iain Murray, Iain Murray, 2012, 1204.3187.

MCMC parameter learning in spatial statistics

Zoubin Ghahramani, Iain Murray, Djc MacKay, 2006 .

Bayesian Learning in Undirected Graphical Models

Zoubin Ghahramani, Iain Murray, Hc Kim, 2003 .

MCMC for Doubly-intractable Distributions

Iain Murray, D. Mackay, Zoubin Ghahramani, 2006, UAI.

Neural Spline Flows

Iain Murray, G. Papamakarios, Conor Durkan, 2019, NeurIPS.

Neural Spline Flows

Iain Murray, G. Papamakarios, Conor Durkan, 2019, Neural Information Processing Systems.

Advances in Markov chain Monte Carlo methods

Iain Murray, 2007 .

Attention as Reward-Driven Optimization of Sensory Processing

Iain Murray, Peggy Seriès, Matthew Chalk, 2013, Neural Computation.

The gravitational force law in the Solar System

Iain Murray, J. Bovy, D. Hogg, 2009 .

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

Iain Murray, David C. Sterratt, George Papamakarios, 2018, AISTATS.

On Contrastive Learning for Likelihood-free Inference

Iain Murray, George Papamakarios, Conor Durkan, 2020, ICML.

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

Iain Murray, George Papamakarios, Iain Murray, 2016 .

Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms pdf

Zoubin Ghahramani, Iain Murray, Iain Murray, 2004, UAI.

MADE: Masked Autoencoder for Distribution Estimation

Hugo Larochelle, Iain Murray, Karol Gregor, 2015, ICML.

Nonparametric Bayesian Density Modeling with Gaussian Processes

Ryan P. Adams, Iain Murray, D. MacKay, 2009, 0912.4896.

Nested sampling for Potts models

Zoubin Ghahramani, Iain Murray, John Skilling, 2005, NIPS.

Maximum Likelihood Training of Score-Based Diffusion Models

Iain Murray, S. Ermon, Conor Durkan, 2021, NeurIPS.

Cubic-Spline Flows pdf

Iain Murray, George Papamakarios, Conor Durkan, 2019, ICML 2019.

Distilling Intractable Generative Models

Iain Murray, George Papamakarios, Iain Murray, 2015 .

The Gaussian Process Density Sampler

Ryan P. Adams, Iain Murray, David J. C. MacKay, 2008, NIPS.

Diverse Ensembles Improve Calibration pdf

Iain Murray, Asa Cooper Stickland, Iain Murray, 2020, ArXiv.

Pseudo-Marginal Slice Sampling

Iain Murray, Matthew M. Graham, Iain Murray, 2015, AISTATS.

Dynamic Evaluation of Transformer Language Models pdf

Steve Renals, Iain Murray, Ben Krause, 2019, ArXiv.

Dynamic Evaluation of Neural Sequence Models pdf

Steve Renals, Ben Krause, Emmanuel Kahembwe, 2017, ICML.

Characterizing response behavior in multisensory perception with conflicting cues

Richard S. Zemel, Iain Murray, Ladan Shams, 2008, NIPS.

DYNAMICAL INFERENCE FROM A KINEMATIC SNAPSHOT: THE FORCE LAW IN THE SOLAR SYSTEM

Iain Murray, J. Bovy, D. Hogg, 2009, 0903.5308.

Markov Chain Truncation for Doubly-Intractable Inference

Colin Wei, Iain Murray, Iain Murray, 2016, AISTATS.

Differentiation of the Cholesky decomposition pdf

Iain Murray, Iain Murray, 2016, ArXiv.

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities

Ryan P. Adams, Iain Murray, David J. C. MacKay, 2009, ICML '09.

Sequential Neural Methods for Likelihood-free Inference pdf

Iain Murray, George Papamakarios, Conor Durkan, 2018, ArXiv.

Mode Normalization pdf

Hakan Bilen, Iain Murray, Lucas Deecke, 2018, ICLR.

Deep Architectures for Articulatory Inversion

Steve Renals, Iain Murray, Benigno Uria, 2012, INTERSPEECH.

Ordering Dimensions with Nested Dropout Normalizing Flows pdf

Iain Murray, Artur Bekasov, Iain Murray, 2020, ArXiv.

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

Marco Fiore, Iain Murray, Paul Patras, 2019, AAAI.

Aye or naw, whit dae ye hink? Scottish independence and linguistic identity on social media

Sharon Goldwater, Iain Murray, Philippa Shoemark, 2017, EACL.

Don’t recommend the obvious: estimate probability ratios

Iain Murray, Wenjie Zhao, Roberto Pellegrini, 2022, RecSys.

Incorporating side information into probabilistic matrix factorization using Gaussian Processes

Ryan P. Adams, Iain Murray, George E. Dahl, 2010 .

A note on the evidence and Bayesian Occam's razor

Zoubin Ghahramani, Iain Murray, Iain Murray, 2005 .

Evaluation methods for topic models

R. Salakhutdinov, Iain Murray, David Mimno, 2009, ICML '09.

Model Criticism in Latent Space

Iain Murray, S. Seth, C. K. Williams, 2017, Bayesian Analysis.

Note on rejection sampling and exact sampling with the Metropolised independence sampler

Iain Murray, Iain Murray, 2004 .