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Disambiguation of "Drton, Mathias"

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Robust Graphical Modeling with t-Distributions.

, and . UAI, page 169-176. AUAI Press, (2009)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Mathias Rafler

Gaussian loop- and Pólya processes: a point process approach. Uni Potsdam, (2009)

Mathias Rausch

Stärkung des Informationsanspruchs durch das Arca-nigra-Verfahren: ein In-camera-Verfahren zur Kontrolle der Informationsgabe. Uni Köln, (2009)

Mathias Guder

Photo-resist stripping with DI/O3 in semiconductor device manufacturing: process chemistry and analytical aspects. Uni Frankfurt Main, (2010)

Mathias Recktenwald

Mathias Linnert

 

Other publications of authors with the same name

Partial Homoscedasticity in Causal Discovery With Linear Models., and . IEEE J. Sel. Areas Inf. Theory, (2023)Nonparametric Reduced Rank Regression., , , and . NIPS, page 1637-1645. (2012)Maximum Likelihood Estimates for Gaussian Mixtures Are Transcendental., , and . MACIS, volume 9582 of Lecture Notes in Computer Science, page 579-590. Springer, (2015)A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence., and . UAI, page 184-191. Morgan Kaufmann, (2003)extttcausalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery., , , , , and . CLeaR, volume 236 of Proceedings of Machine Learning Research, page 609-642. PMLR, (2024)Iterative Conditional Fitting for Gaussian Ancestral Graph Models, and . CoRR, (2012)Graphical Models for Non-Negative Data Using Generalized Score Matching., , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1781-1790. PMLR, (2018)Generalized Score Matching for Non-Negative Data., , and . J. Mach. Learn. Res., (2019)Definite Non-Ancestral Relations and Structure Learning., , and . CoRR, (2021)causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery., , , , , and . CoRR, (2023)