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Denoising neural networks for magnetic resonance spectroscopy


Oct 31, 2022
Natalie Klein, Amber J. Day, Harris Mason, Michael W. Malone, Sinead A. Williamson

* 5 pages with appendix 

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ANOVA exemplars for understanding data drift


Jun 24, 2020
Sinead A. Williamson


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Distributed, partially collapsed MCMC for Bayesian Nonparametrics


Jan 15, 2020
Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead A. Williamson

* Accepted in AISTATS 2020 

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A Nonparametric Bayesian Model for Sparse Temporal Multigraphs


Oct 11, 2019
Elahe Ghalebi, Hamidreza Mahyar, Radu Grosu, Graham W. Taylor, Sinead A. Williamson


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Avoiding Resentment Via Monotonic Fairness


Sep 03, 2019
Guy W. Cole, Sinead A. Williamson


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Sequential Gaussian Processes for Online Learning of Nonstationary Functions


May 24, 2019
Michael Minyi Zhang, Bianca Dumitrascu, Sinead A. Williamson, Barbara E. Engelhardt


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A New Class of Time Dependent Latent Factor Models with Applications


Apr 18, 2019
Sinead A. Williamson, Michael Minyi Zhang, Paul Damien


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Stochastic Blockmodels with Edge Information


Apr 03, 2019
Guy W. Cole, Sinead A. Williamson


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Large-scale Collaborative Filtering with Product Embeddings


Jan 11, 2019
Thom Lake, Sinead A. Williamson, Alexander T. Hawk, Christopher C. Johnson, Benjamin P. Wing

* 15 pages, 5 figures 

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Embarrassingly Parallel Inference for Gaussian Processes


Jun 13, 2018
Michael Minyi Zhang, Sinead A. Williamson


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