activity
20122021
most citedThe Dependence of Routine Bayesian Model Selection Methods on Irrelevant Alternatives

1 citations · 3 across the 4 of their papers we have counts for

collaborators

8 papers

stat.ML20211 cited

Robust estimation of tree structured models

Marta Casanellas, Marina Garrote-López, Piotr Zwiernik

Consider the problem of learning undirected graphical models on trees from corrupted data. Recently Katiyar et al. showed that it is possible to recover trees from noisy binary dat…

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…

stat.CO2019

Estimating linear covariance models with numerical nonlinear algebra

Bernd Sturmfels, Sascha Timme, Piotr Zwiernik

Numerical nonlinear algebra is applied to maximum likelihood estimation for Gaussian models defined by linear constraints on the covariance matrix. We examine the generic case as w…

math.AG2019

Secant varieties of toric varieties arising from simplicial complexes

M. Azeem Khadam, Mateusz Michałek, Piotr Zwiernik

Motivated by the study of the secant variety of the Segre-Veronese variety we propose a general framework to analyze properties of the secant varieties of toric embeddings of affin…

math.ST2019

Brownian motion tree models are toric

Bernd Sturmfels, Caroline Uhler, Piotr Zwiernik

Felsenstein's classical model for Gaussian distributions on a phylogenetic tree is shown to be a toric variety in the space of concentration matrices. We present an exact semialgeb…