3 papers
math.CO2024
Graph-Based Proofs of Indistinguishability of Linear Compartmental Models
Cashous Bortner, John Gilliana, Dev Patel +1
Given experimental data, one of the main objectives of biological modeling is to construct a model which best represents the real world phenomena. In some cases, there could be mul…
math.ST2024
Maximum likelihood degree of the -stochastic blockmodel
Cashous Bortner, Jennifer Garbett, Elizabeth Gross +3
Log-linear exponential random graph models are a specific class of statistical network models that have a log-linear representation. This class includes many stochastic blockmodel…
math.DS2024
Graph-based sufficient conditions for indistinguishability of linear compartmental models
Cashous Bortner, Nicolette Meshkat
An important problem in biological modeling is choosing the right model. Given experimental data, one is supposed to find the best mathematical representation to describe the real-…