3 papers
stat.ML2023
Testing Sparsity Assumptions in Bayesian Networks
Luke Duttweiler, Sally W. Thurston, Anthony Almudevar
Bayesian network (BN) structure discovery algorithms typically either make assumptions about the sparsity of the true underlying network, or are limited by computational constraint…
math.CO2022
Spectral Bayesian Network Theory
Luke Duttweiler, Sally W. Thurston, Anthony Almudevar
A Bayesian Network (BN) is a probabilistic model that represents a set of variables using a directed acyclic graph (DAG). Current algorithms for learning BN structures from data fo…
math.PR2022
A Stochastic Contraction Mapping Theorem
Anthony Almudevar
In this paper we define contractive and nonexpansive properties for adapted stochastic processes which can be used to deduce limiting properties. In general, no…