Iain Murray

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 39

Top Topics

Density Estimation

Gaussian Process

Top Venues

Publications

Efi Karra Taniskidou, Wenjie Zhao, Iain Murray, Roberto Pellegrini
Nudging Neural Click Prediction Models to Pay Attention to Position. CIKM (2023)
Roberto Pellegrini, Wenjie Zhao, Iain Murray
Don't recommend the obvious: estimate probability ratios. RecSys (2022)
Yang Song, Conor Durkan, Iain Murray, Stefano Ermon
Maximum Likelihood Training of Score-Based Diffusion Models. NeurIPS (2021)
James Townsend, Iain Murray
Lossless compression with state space models using bits back coding. CoRR (2021)
Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras
CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting. AAAI (2021)
Tim Dockhorn, James A. Ritchie, Yaoliang Yu, Iain Murray
Density Deconvolution with Normalizing Flows. CoRR (2020)
Asa Cooper Stickland, Iain Murray
Diverse Ensembles Improve Calibration. CoRR (2020)
Conor Durkan, Iain Murray, George Papamakarios
On Contrastive Learning for Likelihood-free Inference. ICML (2020)
Artur Bekasov, Iain Murray
Ordering Dimensions with Nested Dropout Normalizing Flows. CoRR (2020)
Conor Durkan, Iain Murray, George Papamakarios
On Contrastive Learning for Likelihood-free Inference. CoRR (2020)
Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios
Neural Spline Flows. CoRR (2019)
Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras
CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting. CoRR (2019)
Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios
Neural Spline Flows. NeurIPS (2019)
George Papamakarios, David C. Sterratt, Iain Murray
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows. AISTATS (2019)
Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios
Cubic-Spline Flows. CoRR (2019)
James A. Ritchie, Iain Murray
Scalable Extreme Deconvolution. CoRR (2019)
Asa Cooper Stickland, Iain Murray
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning. ICML (2019)
Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals
Dynamic Evaluation of Transformer Language Models. CoRR (2019)
Lucas Deecke, Iain Murray, Hakan Bilen
Mode Normalization. ICLR (Poster) (2019)
Asa Cooper Stickland, Iain Murray
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning. CoRR (2019)
Conor Durkan, George Papamakarios, Iain Murray
Sequential Neural Methods for Likelihood-free Inference. CoRR (2018)
Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals
Dynamic Evaluation of Neural Sequence Models. ICML (2018)
George Papamakarios, David C. Sterratt, Iain Murray
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows. CoRR (2018)
Lucas Deecke, Iain Murray, Hakan Bilen
Mode Normalization. CoRR (2018)
Artur Bekasov, Iain Murray
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting. CoRR (2018)
Colin Wei, Iain Murray
Markov Chain Truncation for Doubly-Intractable Inference. AISTATS (2017)
George Papamakarios, Iain Murray, Theo Pavlakou
Masked Autoregressive Flow for Density Estimation. NIPS (2017)
Ben Krause, Iain Murray, Steve Renals, Liang Lu
Multiplicative LSTM for sequence modelling. ICLR (Workshop) (2017)
Philippa Shoemark, Debnil Sur, Luke Shrimpton, Iain Murray, Sharon Goldwater
Aye or naw, whit dae ye hink? Scottish independence and linguistic identity on social media. EACL (1) (2017)
George Papamakarios, Theo Pavlakou, Iain Murray
Masked Autoregressive Flow for Density Estimation. CoRR (2017)
Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals
Dynamic Evaluation of Neural Sequence Models. CoRR (2017)
George Papamakarios, Iain Murray
Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation. CoRR (2016)
Iain Murray
Differentiation of the Cholesky decomposition. CoRR (2016)
George Papamakarios, Iain Murray
Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation. NIPS (2016)
Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle
Neural Autoregressive Distribution Estimation. J. Mach. Learn. Res. 17 (2016)
Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle
Neural Autoregressive Distribution Estimation. CoRR (2016)
Iain Murray, Matthew M. Graham
Pseudo-Marginal Slice Sampling. AISTATS (2016)
Colin Wei, Iain Murray
Markov Chain Truncation for Doubly-Intractable Inference. CoRR (2016)
Ben Krause, Liang Lu, Iain Murray, Steve Renals
Multiplicative LSTM for sequence modelling. CoRR (2016)
Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle
MADE: Masked Autoencoder for Distribution Estimation. ICML (2015)
Benigno Uria, Iain Murray, Steve Renals, Cassia Valentini-Botinhao, John Bridle
Modelling acoustic feature dependencies with artificial neural networks: Trajectory-RNADE. ICASSP (2015)
Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle
MADE: Masked Autoencoder for Distribution Estimation. CoRR (2015)
Ryan Prescott Adams, George E. Dahl, Iain Murray
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes. CoRR (2014)
Benigno Uria, Iain Murray, Hugo Larochelle
A Deep and Tractable Density Estimator. ICML (2014)
Robert Nishihara, Iain Murray, Ryan P. Adams
Parallel MCMC with generalized elliptical slice sampling. J. Mach. Learn. Res. 15 (1) (2014)
Benigno Uria, Iain Murray, Hugo Larochelle
RNADE: The real-valued neural autoregressive density-estimator. NIPS (2013)
Benigno Uria, Iain Murray, Hugo Larochelle
A Deep and Tractable Density Estimator. CoRR (2013)
Jakob H. Macke, Iain Murray, Peter E. Latham
Estimation Bias in Maximum Entropy Models. Entropy 15 (8) (2013)
Razvan Ranca, Iain Murray
A Composable Strategy for Shredded Document Reconstruction. CAIP (2) (2013)
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray
A framework for evaluating approximation methods for Gaussian process regression. J. Mach. Learn. Res. 14 (1) (2013)
Benigno Uria, Iain Murray, Hugo Larochelle
NADE: The real-valued neural autoregressive density-estimator. CoRR (2013)
Matthew Chalk, Iain Murray, Peggy Seriès
Attention as Reward-Driven Optimization of Sensory Processing. Neural Comput. 25 (11) (2013)
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray
A Framework for Evaluating Approximation Methods for Gaussian Process Regression CoRR (2012)
Iain Murray, Zoubin Ghahramani
Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms CoRR (2012)
Benigno Uria, Iain Murray, Steve Renals, Korin Richmond
Deep Architectures for Articulatory Inversion. INTERSPEECH (2012)
Hugo Larochelle, Iain Murray
The Neural Autoregressive Distribution Estimator. AISTATS (2011)
Jakob H. Macke, Iain Murray, Peter E. Latham
How biased are maximum entropy models? NIPS (2011)
Iain Murray, Ryan Prescott Adams, David J. C. MacKay
Elliptical slice sampling. AISTATS (2010)
Ryan Prescott Adams, George E. Dahl, Iain Murray
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes CoRR (2010)
Ryan Prescott Adams, George E. Dahl, Iain Murray
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes. UAI (2010)
Iain Murray, Ryan Prescott Adams
Slice sampling covariance hyperparameters of latent Gaussian models. NIPS (2010)
Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno
Evaluation methods for topic models. ICML (2009)
Ryan Prescott Adams, Iain Murray, David J. C. MacKay
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities. ICML (2009)
Ruslan Salakhutdinov, Iain Murray
On the quantitative analysis of deep belief networks. ICML (2008)
Ryan Prescott Adams, Iain Murray, David J. C. MacKay
The Gaussian Process Density Sampler. NIPS (2008)
Rama Natarajan, Iain Murray, Ladan Shams, Richard S. Zemel
Characterizing response behavior in multisensory perception with conflicting cues. NIPS (2008)
Iain Murray, Ruslan Salakhutdinov
Evaluating probabilities under high-dimensional latent variable models. NIPS (2008)
Iain Murray, Zoubin Ghahramani, David J. C. MacKay
MCMC for Doubly-intractable Distributions. UAI (2006)
Iain Murray, Edward Lloyd Snelson
A Pragmatic Bayesian Approach to Predictive Uncertainty. MLCW (2005)
Iain Murray, David J. C. MacKay, Zoubin Ghahramani, John Skilling
Nested sampling for Potts models. NIPS (2005)
Iain Murray, Zoubin Ghahramani
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms. UAI (2004)