Mathias Drton - researchr alias

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Viewing Publication 1 - 27 from 27

2023

2022

Learning linear non-Gaussian polytree modelsDaniele Tramontano, Anthea Monod, Mathias Drton. uai 2022: 1960-1969 [doi]

Graphical Representations for Algebraic Constraints of Linear Structural Equations ModelsThijs van Ommen, Mathias Drton. pgm 2022: 409-420 [doi]

2021

Confidence in causal discovery with linear causal modelsDavid Strieder, Tobias Freidling, Stefan Haffner, Mathias Drton. uai 2021: 1217-1226 [doi]

CorDiffViz: an R package for visualizing multi-omics differential correlation networksShiqing Yu, Mathias Drton, Daniel E. L. Promislow, Ali Shojaie. bmcbi, 22(1):486, 2021. [doi]

2020

Structure Learning for Cyclic Linear Causal ModelsCarlos Améndola, Philipp Dettling, Mathias Drton, Federica Onori, Jun Wu. uai 2020: 408 [doi]

Statistical Significance in High-dimensional Linear Mixed ModelsLina Lin, Mathias Drton, Ali Shojaie. fods 2020: 171-181 [doi]

2019

Generalized Score Matching for Non-Negative DataShiqing Yu, Mathias Drton, Ali Shojaie. jmlr, 20, 2019. [doi]

2018

Algebraic tests of general Gaussian latent tree modelsDennis Leung, Mathias Drton. nips 2018: 6301-6310 [doi]

Graphical Models for Non-Negative Data Using Generalized Score MatchingShiqing Yu, Mathias Drton, Ali Shojaie. aistats 2018: 1781-1790 [doi]

2016

Efficient computation of the Bergsma-Dassios sign covarianceLuca Weihs, Mathias Drton, Dennis Leung. cstat, 31(1):315-328, 2016. [doi]

2015

Maximum Likelihood Estimates for Gaussian Mixtures Are TranscendentalCarlos Améndola, Mathias Drton, Bernd Sturmfels. macis 2016: 579-590 [doi]

2013

PC algorithm for nonparanormal graphical modelsNaftali Harris, Mathias Drton. jmlr, 14(1):3365-3383, 2013. [doi]

2012

Nonparametric Reduced Rank RegressionRina Foygel, Michael Horrell, Mathias Drton, John D. Lafferty. nips 2012: 1637-1645 [doi]

2010

On a Parametrization of Positive Semidefinite Matrices with ZerosMathias Drton, Josephine Yu. siammax, 31(5):2665-2680, 2010. [doi]

Extended Bayesian Information Criteria for Gaussian Graphical ModelsRina Foygel, Mathias Drton. nips 2010: 604-612 [doi]

2009

Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated ErrorsMathias Drton, Michael Eichler, Thomas S. Richardson. jmlr, 10:2329-2348, 2009. [doi]

Robust Graphical Modeling with t-DistributionsMichael Finegold, Mathias Drton. uai 2009: 169-176 [doi]

2008

Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance ModelsMathias Drton, Thomas S. Richardson. jmlr, 9:893-914, 2008. [doi]

2006

Computing all roots of the likelihood equations of seemingly unrelated regressionsMathias Drton. JSC, 41(2):245-254, 2006. [doi]

2004

Iterative Conditional Fitting for Gaussian Ancestral Graph ModelsMathias Drton, Thomas S. Richardson. uai 2004: 130-137 [doi]

2003

A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal IndependenceMathias Drton, Thomas S. Richardson. uai 2003: 184-191

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