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Deterministic variables are variables that are fully explained by one or more parent variables. They commonly arise when a variable has been algebraically constructed from one or more parent variables, as with composite variables, and in…

Tropical geometry is a piecewise linear "shadow" of algebraic geometry. It allows for the computation of several cohomological invariants of an algebraic variety. In particular, its application to enumerative algebraic geometry led to…

Algebraic Geometry · Mathematics 2012-06-12 Florian Block

Sampling algorithms, hypergraph degree sequences, and polytopes play a crucial role in statistical analysis of network data. This article offers a brief overview of open problems in this area of discrete mathematics from the point of view…

Discrete Mathematics · Computer Science 2016-01-11 Sonja Petrović

Estimating the structure of directed acyclic graphs (DAGs, also known as Bayesian networks) is a challenging problem since the search space of DAGs is combinatorial and scales superexponentially with the number of nodes. Existing approaches…

Machine Learning · Statistics 2018-11-06 Xun Zheng , Bryon Aragam , Pradeep Ravikumar , Eric P. Xing

Directed acyclic graph (DAG) models are widely used to represent causal relationships among random variables in many application domains. This paper studies a special class of non-Gaussian DAG models, where the conditional variance of each…

Machine Learning · Statistics 2021-11-03 Wei Zhou , Xin He , Wei Zhong , Junhui Wang

In this paper we investigate the geometry of a discrete Bayesian network whose graph is a tree all of whose variables are binary and the only observed variables are those labeling its leaves. We provide the full geometric description of…

Statistics Theory · Mathematics 2011-10-20 Piotr Zwiernik , Jim Q. Smith

Learning causal relationships between variables is a fundamental task in causal inference and directed acyclic graphs (DAGs) are a popular choice to represent the causal relationships. As one can recover a causal graph only up to its Markov…

Machine Learning · Computer Science 2024-02-14 Davin Choo , Kirankumar Shiragur

Learning the structure of Directed Acyclic Graphs (DAGs) presents a significant challenge due to the vast combinatorial search space of possible graphs, which scales exponentially with the number of nodes. Recent advancements have redefined…

Machine Learning · Computer Science 2024-11-01 Klea Ziu , Slavomír Hanzely , Loka Li , Kun Zhang , Martin Takáč , Dmitry Kamzolov

In this paper we investigate the use of staged tree models for discrete longitudinal data. Staged trees are a type of probabilistic graphical model for finite sample space processes. They are a natural fit for longitudinal data because a…

Methodology · Statistics 2024-01-10 Jack Storror Carter , Manuele Leonelli , Eva Riccomagno , Alessandro Ugolini

We give an introduction to Tropical Geometry and prove some results in Tropical Intersection Theory. The first part of this paper is an introduction to tropical geometry aimed at researchers in Algebraic Geometry from the point of view of…

Algebraic Geometry · Mathematics 2010-06-22 Eric Katz

The main aim of this work is to present the interpretation of the Ising type models as a kind of field theory in the framework of noncommutative geometry. We present the method and construct sample models of field theory on discrete spaces…

High Energy Physics - Theory · Physics 2009-10-22 Andrzej Sitarz

Identification theory for causal effects in causal models associated with hidden variable directed acyclic graphs (DAGs) is well studied. However, the corresponding algorithms are underused due to the complexity of estimating the…

Machine Learning · Statistics 2022-10-17 Rohit Bhattacharya , Razieh Nabi , Ilya Shpitser

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

Bayesian networks are a widely-used class of probabilistic graphical models capable of representing symmetric conditional independence between variables of interest using the topology of the underlying graph. For categorical variables, they…

Machine Learning · Statistics 2022-10-07 Gherardo Varando , Federico Carli , Manuele Leonelli

Tropical Differential Algebraic Geometry considers difficult or even intractable problems in Differential Equations and tries to extract information on their solutions from a restricted structure of the input. The Fundamental Theorem of…

We consider a binary response which is potentially affected by a set of continuous variables. Of special interest is the causal effect on the response due to an intervention on a specific variable. The latter can be meaningfully determined…

Methodology · Statistics 2020-09-11 Federico Castelletti , Guido Consonni

The paper gives an overview of recent advances in structural equation modeling. A structural equation model is a multivariate statistical model that is determined by a mixed graph, also known as a path diagram. Our focus is on the…

Statistics Theory · Mathematics 2016-12-20 Mathias Drton

We construct polyhedral families of valuations on the branching algebra of a morphism of reductive groups. This establishes a connection between the combinatorial rules for studying a branching problem and the tropical geometry of the…

Algebraic Geometry · Mathematics 2012-08-29 Christopher Manon

Tropical algebraic geometry is an active new field of mathematics that establishes and studies some very general principles to translate algebro-geometric problems into purely combinatorial ones. This expository paper gives an introduction…

Algebraic Geometry · Mathematics 2007-05-23 Andreas Gathmann

This paper is devoted to constructing and studying exactly solvable dynamical systems in discrete time obtained from some algebraic operations on matrices, to reductions of such systems leading to classical field theory models in…

solv-int · Physics 2008-02-03 I. G. Korepanov