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01/28/2022
Family-wise error rate control in Gaussian graphical model selection via Distributionally Robust Optimization
Recently, a special case of precision matrix estimation based on a distr...
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05/14/2021
Learning Gaussian Graphical Models with Latent Confounders
Gaussian Graphical models (GGM) are widely used to estimate the network ...
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10/07/2019
Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes
The covariance structure of multivariate functional data can be highly c...
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05/22/2019
Distributionally Robust Formulation and Model Selection for the Graphical Lasso
Building on a recent framework for distributionally robust optimization ...
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10/30/2017
Communication-Avoiding Optimization Methods for Massive-Scale Graphical Model Structure Learning
Undirected graphical models compactly represent the structure of large, ...
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01/28/2016
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks
Experiments in particle physics produce enormous quantities of data that...
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07/20/2013