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20122026
most citedThe Dependence of Routine Bayesian Model Selection Methods on Irrelevant Alternatives

1 citations · 3 across the 6 of their papers we have counts for

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8 papers · 1 filter

math.ST2024

Learning latent tree models with small query complexity

Luc Devroye, Gabor Lugosi, Piotr Zwiernik

We consider the problem of structure recovery in a graphical model of a tree where some variables are latent. Specifically, we focus on the Gaussian case, which can be reformulated…

math.ST2024

Property testing in graphical models: testing small separation numbers

Luc Devroye, Gábor Lugosi, Piotr Zwiernik

In many statistical applications, the dimension is too large to handle for standard high-dimensional machine learning procedures. This is particularly true for graphical models, wh…

math.ST2023

Entropic covariance models

Piotr Zwiernik

In covariance matrix estimation, one of the challenges lies in finding a suitable model and an efficient estimation method. Two commonly used modelling approaches in the literature…

math.ST2023

Positivity in Linear Gaussian Structural Equation Models

Asad Lodhia, Jan-Christian Hütter, Caroline Uhler +1

We study a notion of positivity of Gaussian directed acyclic graphical models corresponding to a non-negativity constraint on the coefficients of the associated structural equation…

math.ST20211 cited

Likelihood Geometry of Correlation Models

Carlos Améndola, Piotr Zwiernik

Correlation matrices are standardized covariance matrices. They form an affine space of symmetric matrices defined by setting the diagonal entries to one. We study the geometry of…

math.ST2020

Dependence in elliptical partial correlation graphs

David Rossell, Piotr Zwiernik

The Gaussian model equips strong properties that facilitate studying and interpreting graphical models. Specifically it reduces conditional independence and the study of positive a…