9 citations · 10 across the 3 of their papers we have counts for
8 papers
Learning Barycenters from Signature Matrices
Carlos Améndola, Leonard Schmitz
The expected signature of a family of paths need not be a signature of a path itself. Motivated by this, we consider the notion of a Lie group barycenter introduced by Buser and Ka…
The Maximum Likelihood Degree of Toric Models is Monotonic
Carlos Améndola, Janike Oldekop, Maximilian Wiesmann
We settle a conjecture by Coons and Sullivant stating that the maximum likelihood (ML) degree of a facial submodel of a toric model is at most the ML degree of the model itself. We…
One-dimensional Discrete Models of Maximum Likelihood Degree One
Carlos Améndola, Viet Duc Nguyen, Janike Oldekop
We settle a conjecture by Bik and Marigliano stating that the degree of a one-dimensional discrete model with rational maximum likelihood estimator is bounded above by a linear fun…
Maximum likelihood estimation of log-affine models using detailed-balanced reaction networks
Oskar Henriksson, Carlos Améndola, Jose Israel Rodriguez +1
A fundamental question in the field of molecular computation is what computational tasks a biochemical system can carry out. In this work, we focus on the problem of finding the ma…
On the maximum likelihood degree for Gaussian graphical models
Carlos Améndola, Rodica Andreea Dinu, Mateusz Michałek +1
In this paper we revisit the likelihood geometry of Gaussian graphical models. We give a detailed proof that the ML-degree behaves monotonically on induced subgraphs. Furthermore,…
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…