Ryan Prescott Adams

Publication Activity (10 Years)

Years Active: 2008-2015
Publications (10 Years): 0

Top Topics

Pattern Discovery

Singly Connected

Restricted Boltzmann Machine

Gaussian Process

Top Venues

Publications

Dougal Maclaurin, Ryan Prescott Adams
Firefly Monte Carlo: Exact MCMC with Subsets of Data. IJCAI (2015)
Ryan Prescott Adams, George E. Dahl, Iain Murray
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes. CoRR (2014)
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
Freeze-Thaw Bayesian Optimization. CoRR (2014)
Xi Alice Gao, Andrew Mao, Yiling Chen, Ryan Prescott Adams
Trick or treat: putting peer prediction to the test. EC (2014)
James Y. Zou, Daniel J. Hsu, David C. Parkes, Ryan Prescott Adams
Contrastive Learning Using Spectral Methods. NIPS (2013)
Oren Rippel, Ryan Prescott Adams
High-Dimensional Probability Estimation with Deep Density Models CoRR (2013)
Jasper Snoek, Richard S. Zemel, Ryan Prescott Adams
A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data. NIPS (2013)
Andrew Gordon Wilson, Ryan Prescott Adams
Gaussian Process Covariance Kernels for Pattern Discovery and Extrapolation CoRR (2013)
Nils Napp, Ryan Prescott Adams
Message Passing Inference with Chemical Reaction Networks. NIPS (2013)
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
Multi-Task Bayesian Optimization. NIPS (2013)
Andrew Gordon Wilson, Ryan Prescott Adams
Gaussian Process Kernels for Pattern Discovery and Extrapolation. ICML (3) (2013)
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
On Nonparametric Guidance for Learning Autoencoder Representations. AISTATS (2012)
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zemel
Randomized Optimum Models for Structured Prediction. AISTATS (2012)
Jeroen Chua, Inmar E. Givoni, Ryan Prescott Adams, Brendan J. Frey
Learning structural element patch models with hierarchical palettes. CVPR (2012)
George E. Dahl, Ryan Prescott Adams, Hugo Larochelle
Training Restricted Boltzmann Machines on Word Observations. ICML (2012)
Daniel Tarlow, Ryan Prescott Adams
Revisiting uncertainty in graph cut solutions. CVPR (2012)
Daniel Tarlow, Kevin Swersky, Richard S. Zemel, Ryan Prescott Adams, Brendan J. Frey
Fast Exact Inference for Recursive Cardinality Models CoRR (2012)
George E. Dahl, Ryan Prescott Adams, Hugo Larochelle
Training Restricted Boltzmann Machines on Word Observations CoRR (2012)
Daniel Tarlow, Kevin Swersky, Richard S. Zemel, Ryan Prescott Adams, Brendan J. Frey
Fast Exact Inference for Recursive Cardinality Models. UAI (2012)
Jasper Snoek, Hugo Larochelle, Ryan Prescott Adams
Practical Bayesian Optimization of Machine Learning Algorithms CoRR (2012)
Ryan Prescott Adams, Richard S. Zemel
Ranking via Sinkhorn Propagation CoRR (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)
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghahramani
Learning the Structure of Deep Sparse Graphical Models. AISTATS (2010)
Ryan Prescott Adams, Zoubin Ghahramani, Michael I. Jordan
Tree-Structured Stick Breaking for Hierarchical Data. NIPS (2010)
Ryan Prescott Adams, Zoubin Ghahramani
Archipelago: nonparametric Bayesian semi-supervised learning. ICML (2009)
Ryan Prescott Adams, Iain Murray, David J. C. MacKay
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities. ICML (2009)
Ryan Prescott Adams, Oliver Stegle
Gaussian process product models for nonparametric nonstationarity. ICML (2008)
Ryan Prescott Adams, Iain Murray, David J. C. MacKay
The Gaussian Process Density Sampler. NIPS (2008)