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Estimating the structure of Bayesian networks as directed acyclic graphs (DAGs) from observational data is a fundamental challenge, particularly in causal discovery. Bayesian approaches excel by quantifying uncertainty and addressing…

Machine Learning · Computer Science 2026-02-17 Edwin V. Bonilla , Pantelis Elinas , He Zhao , Maurizio Filippone , Vassili Kitsios , Terry O'Kane

We define Gaussian graphical models on directed acyclic graphs with coloured vertices and edges, calling them RDAG (restricted directed acyclic graph) models. If two vertices or edges have the same colour, their parameters in the model must…

Statistics Theory · Mathematics 2022-05-30 Visu Makam , Philipp Reichenbach , Anna Seigal

We propose an algebraic geometric framework to study the expressivity of linear activation neural networks. A particular quantity of neural networks that has been actively studied is the number of linear regions, which gives a…

Machine Learning · Computer Science 2024-10-10 Paul Lezeau , Thomas Walker , Yueqi Cao , Shiv Bhatia , Anthea Monod

We consider the problem of learning the underlying causal structure among a set of variables, which are assumed to follow a Bayesian network or, more specifically, a linear recursive structural equation model (SEM) with the associated…

Statistics Theory · Mathematics 2025-08-05 Anamitra Chaudhuri , Anirban Bhattacharya , Yang Ni

We study the behavior of phylogenetic tree shapes in the tropical geometric interpretation of tree space. Tree shapes are formally referred to as tree topologies; a tree topology can also be thought of as a tree combinatorial type, which is…

Combinatorics · Mathematics 2023-01-25 Bo Lin , Anthea Monod , Ruriko Yoshida

Tropical varieties play an important role in algebraic geometry. The Bergman complex B(M) and the positive Bergman complex B+(M) of an oriented matroid M generalize to matroids the notions of the tropical variety and positive tropical…

Combinatorics · Mathematics 2007-05-23 Federico Ardila , Victor Reiner , Lauren Williams

Cycle polytopes of matroids have been introduced in combinatorial optimization as a generalization of important classes of polyhedral objects like cut polytopes and Eulerian subgraph polytopes associated to graphs. Here we start an…

Combinatorics · Mathematics 2021-05-04 Tim Römer , Sara Saeedi Madani

We consider, for complete bipartite graphs, the convex hulls of characteristic vectors of all matchings, extended by a binary entry indicating whether the matching contains two specific edges. These polytopes are associated to the quadratic…

Discrete Mathematics · Computer Science 2019-04-09 Matthias Walter

A directed acyclic graph (DAG) is the most common graphical model for representing causal relationships among a set of variables. When restricted to using only observational data, the structure of the ground truth DAG is identifiable only…

Data Structures and Algorithms · Computer Science 2018-09-12 AmirEmad Ghassami , Saber Salehkaleybar , Negar Kiyavash , Kun Zhang

We describe Galois connections which arise between two kinds of combinatorial structures, both of which generalize trees with labelled leaves, and then apply those connections to a family of polytopes. The graphs we study can be imbued with…

Combinatorics · Mathematics 2020-07-27 Stefan Forcey , Drew Scalzo

This is a survey article written for the Jahresberichte der DMV. Tropical geometry can be viewed as an efficient combinatorial tool to study degenerations in algebraic geometry. Abstract tropical curves are essentially metric graphs, and…

Algebraic Geometry · Mathematics 2020-03-23 Hannah Markwig

Tropical varieties are polyhedral shadows of classical varieties. The purpose of these expository notes is to explain the origin of this polyhedral complex structure from the perspective of Gr\"obner bases. To appear in the proceedings of…

Commutative Algebra · Mathematics 2013-02-22 Diane Maclagan

Threshold graphs are recursive deterministic network models that have been proposed for describing certain economic and social interactions. One drawback of this graph family is that it has limited generative attachment rules. To mitigate…

Social and Information Networks · Computer Science 2018-05-24 Vida Ravanmehr , Gregory J. Puleo , Sadegh Bolouki , Olgica Milenkovic

Trees with many leaves have applications on broadcasting, which is a method in networks for transferring a message to all recipients simultaneously. Internal nodes of a broadcasting tree require more expensive technology, because they have…

Data Structures and Algorithms · Computer Science 2021-11-29 Cristina G. Fernandes , Carla N. Lintzmayer

We give an overview of recently implemented polymake features for computations in tropical geometry. The main focus is on explicit examples rather than technical explanations. Our computations employ tropical hypersurfaces, moduli of…

Algebraic Geometry · Mathematics 2018-10-30 Simon Hampe , Michael Joswig

We consider the class of graphs for which the edge connectivity is equal to the maximum number of edge-disjoint spanning trees, and the natural generalization to matroids, where the cogirth is equal to the number of disjoint bases. We…

Combinatorics · Mathematics 2014-02-10 Robert F. Bailey , Mike Newman , Brett Stevens

Directed acyclic graphs (DAGs) are commonly used to represent causal relationships among random variables in graphical models. Applications of these models arise in the study of physical, as well as biological systems, where directed edges…

Machine Learning · Statistics 2009-12-01 Ali Shojaie , George Michailidis

We associate root polytopes to directed graphs and study them by using ribbon structures. Most attention is paid to what we call the semi-balanced case, i.e., when each cycle has the same number of edges pointing in the two directions.…

Combinatorics · Mathematics 2024-08-16 Tamás Kálmán , Lilla Tóthmérész

This work tackles the problem of characterizing and understanding the decision boundaries of neural networks with piecewise linear non-linearity activations. We use tropical geometry, a new development in the area of algebraic geometry, to…

Machine Learning · Computer Science 2022-08-24 Motasem Alfarra , Adel Bibi , Hasan Hammoud , Mohamed Gaafar , Bernard Ghanem

Pair-copula Bayesian networks (PCBNs) are a novel class of multivariate statistical models, which combine the distributional flexibility of pair-copula constructions (PCCs) with the parsimony of conditional independence models associated…

Methodology · Statistics 2012-11-27 Alexander Bauer , Claudia Czado
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