most citedMatroid Stratification of ML Degrees of Independence Models

2 citations · 2 across the 5 of their papers we have counts for

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5 papers

math.CO2026

Posets of trek polynomials for directed trees

Marina Garrote-López, Nataliia Kushnerchuk, Liam Solus

When a variety equals the image of a polynomial map whose coordinate functions are combinatorial generating polynomials (i.e.~polynomials enumerating combinatorial object…

math.CO2026

On unirational varieties with poset parameterizations

Marina Garrote-López, Nataliia Kushnerchuk, Liam Solus

We use partially ordered sets (posets) to provide a canonical parameterization for the Zariski closure of the image of a semialgebraic set under a rational map whose coordinate fun…

math.ST2026

Discrete-time, discrete-state multistate Markov models from the perspective of algebraic statistics

Dario Gasbarra, Kaie Kubjas, Sangita Kulathinal +3

We study discrete-time, discrete-state multistate Markov models from the perspective of algebraic statistics. These models are widely studied in event history analysis, and are cha…

math.ST2026

Identifiability in Graphical Discrete Lyapunov Models

Cecilie Olesen Recke, Sarah Lumpp, Nataliia Kushnerchuk +4

In this paper, we study discrete Lyapunov models, which consist of steady-state distributions of first-order vector autoregressive models. The parameter matrix of such a model enco…

math.ST2023★ 2 cited

Matroid Stratification of ML Degrees of Independence Models

Oliver Clarke, Serkan Hoşten, Nataliia Kushnerchuk +1

We study the maximum likelihood (ML) degree of discrete exponential independence models and models defined by the second hypersimplex. For models with two independent variables, we…