In covariance matrix estimation, one of the challenges lies in finding a...
We study a notion of positivity of Gaussian directed acyclic graphical m...
A frequent challenge when using graphical models in applications is that...
A seminal result in the ICA literature states that for AY = ε, if
the co...
Positive dependence is present in many real world data sets and has appe...
We study the problem of maximum likelihood estimation given one data sam...
Consider the problem of learning undirected graphical models on trees fr...
Correlation matrices are standardized covariance matrices. They form an
...
The notion of multivariate total positivity has proved to be useful in
f...
The Gaussian model is equipped with strong properties that facilitate
st...
Numerical nonlinear algebra is applied to maximum likelihood estimation ...
We consider the problem of the identification of stationary solutions to...
We study the problem of recovering the structure underlying large Gaussi...
We study binary distributions that are multivariate totally positive of ...
Felsenstein's classical model for Gaussian distributions on a phylogenet...
Latent tree models are graphical models defined on trees, in which only ...
Gaussian latent tree models, or more generally, Gaussian latent forest m...