26 citations · 28 across the 7 of their papers we have counts for
9 papers
Universal Varieties for Signatures of Membranes
Carlos Améndola, Gabriel Riffo, Leonard Schmitz
Membranes are sufficiently smooth vector-valued functions defined on the unit square, widely used in applications such as interpolation of image data. The signature of a membrane i…
Algebraic statistics of Hüsler-Reiss graphical models in multivariate extremes
Carlos Améndola, Jane Ivy Coons, Alexandros Grosdos +1
The field of extreme value statistics is concerned with modeling and predicting rare events. In a Hüsler-Reiss graphical model, a graph represents extremal conditional independence…
Signature Varieties of Splines
Carlos Améndola, Felix Lotter, Leonard Schmitz
Splines are central objects for the interpolation of discrete data via piecewise smooth paths. Their iterated-integral signature is an infinite collection of tensors which characte…
Structural Identifiability of Graphical Continuous Lyapunov Models
Carlos Améndola, Tobias Boege, Benjamin Hollering +1
We prove two characterizations of model equivalence of acyclic graphical continuous Lyapunov models (GCLMs) with uncorrelated noise. The first result shows that two graphs are mode…
A PC Algorithm for Max-Linear Bayesian Networks
Carlos Améndola, Benjamin Hollering, Francesco Nowell
Max-linear Bayesian networks (MLBNs) are a relatively recent class of structural equation models which arise when the random variables involved have heavy-tailed distributions. Unl…
Tropical Fréchet Means: a polyhedral approach to exact optimization
Kamillo Ferry, Bo Lin, Carlos Améndola +2
The Fréchet mean is a fundamental notion of central tendency defined as a minimizer of a sum of squared distances in a general metric space. In this paper, we study Fréchet means i…
Tropical combinatorics of max-linear Bayesian networks
Carlos Améndola, Kamillo Ferry
A polytrope is a tropical polyhedron that is also classically convex. We study the tropical combinatorial types of polytropes associated to weighted directed acyclic graphs (DAGs).…
Markov Equivalence of Max-Linear Bayesian Networks
Carlos Améndola, Ben Hollering, Seth Sullivant +1
Max-linear Bayesian networks have emerged as highly applicable models for causal inference via extreme value data. However, conditional independence (CI) for max-linear Bayesian ne…
Conditional Independence in Max-linear Bayesian Networks
Carlos Améndola, Claudia Klüppelberg, Steffen Lauritzen +1
Motivated by extreme value theory, max-linear Bayesian networks have been recently introduced and studied as an alternative to linear structural equation models. However, for max-l…