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Non-Gaussian outcomes are often modeled using members of the so-called exponential family. Notorious members are the Bernoulli model for binary data, leading to logistic regression, and the Poisson model for count data, leading to Poisson…

In 1981, Andr\'e Joyal provided a combinatorial interpretation of the algebra of formal power series, a central gadget in the toolkit of enumerative combinatorics. In Joyal's theory of species of structures, combinatorial species (like…

Combinatorics · Mathematics 2023-06-07 Arthur Gonçalves Fidalgo

The family of planar graphs is a particularly important family and models many real-world networks. In this paper, we propose a principled framework based on the widely-known Apollonian packing process to generate new planar network, i.e.,…

Physics and Society · Physics 2023-12-27 Fei Ma , Jinzhi Ouyang , Ping Wang , Haobin Shi , Wei Pan

We study random trees which are invariant in law under the operation of contracting each edge independently with probability $p\in(0,1)$. We show that all such trees can be constructed through Poissonian sampling from a certain class of…

Probability · Mathematics 2018-06-20 Olivier Hénard , Pascal Maillard

We provide new examples of the asymptotic counting for the number of subsets on groups of given size which are free of certain configurations. These examples include sets without solutions to equations in non-abelian groups, and linear…

Combinatorics · Mathematics 2016-02-08 Juanjo Rué , Oriol Serra , Lluís Vena

We define a model for random (abstract) cell complexes (CCs), similiar to the well-known Erd\H{o}s-R\'enyi model for graphs and its extensions for simplicial complexes. To build a random cell complex, we first draw from an Erd\H{o}s-R\'enyi…

Data Structures and Algorithms · Computer Science 2025-11-21 Josef Hoppe , Michael T. Schaub

We consider inference from non-random samples in data-rich settings where high-dimensional auxiliary information is available both in the sample and the target population, with survey inference being a special case. We propose a regularized…

Methodology · Statistics 2021-04-13 Yutao Liu , Andrew Gelman , Qixuan Chen

We consider planar maps adjusted with a (regular critical) Boltzmann distribution and show that the expected number of pattern occurrences of a given map is asymptotically linear when the number n of edges goes to infinity. The main…

Combinatorics · Mathematics 2019-05-20 Michael Drmota , Benedikt Stufler

The B-series composition theorem has been an important topic in numerical analysis of ordinary differential equations for the past-half century. Traditional proofs of this theorem rely on labelled trees, whereas recent developments in…

Numerical Analysis · Mathematics 2024-09-16 John C. Butcher , Taketomo Mitsui , Yuto Miyatake , Shun Sato

Polynomial regression is widely used and can help to express nonlinear patterns. However, considering very high polynomial orders may lead to overfitting and poor extrapolation ability for unseen data. The paper presents a method for…

Machine Learning · Computer Science 2023-08-01 Andrei Ivanov , Stefan Maria Ailuro

We prove local convergence results for the uniformly random, labelled or unlabelled, graphs from subcritical families. As an example special case, we prove Benjamini-Schramm convergence for the uniform random unlabelled tree. We introduce a…

Combinatorics · Mathematics 2016-11-28 Agelos Georgakopoulos , Stephan Wagner

Multivariate distributions often carry latent structures that are difficult to identify and estimate, and which better reflect the data generating mechanism than extrinsic structures exhibited simply by the raw data. In this paper, we…

Methodology · Statistics 2025-04-16 Bryon Aragam , Ruiyi Yang

We describe a combinatorial approach for investigating properties of rational numbers. The overall approach rests on structural bijections between rational numbers and familiar combinatorial objects, namely rooted trees. We emphasize that…

Combinatorics · Mathematics 2012-01-13 Edinah K. Gnang , Chetan Tonde

We consider the process of uncovering the vertices of a random labeled tree according to their labels. First, a labeled tree with $n$ vertices is generated uniformly at random. Thereafter, the vertices are uncovered one by one, in order of…

Probability · Mathematics 2023-01-03 Benjamin Hackl , Alois Panholzer , Stephan Wagner

We introduce and study the model of simply generated non-crossing partitions, which are, roughly speaking, chosen at random according to a sequence of weights. This framework encompasses the particular case of uniform non-crossing…

Probability · Mathematics 2017-06-30 Igor Kortchemski , Cyril Marzouk

In this document we achieve exact and asymptotic enumeration of words, compositions over a finite group, and/or integer compositions characterized by local restrictions and, separately, subsequence pattern avoidance. We also count…

Combinatorics · Mathematics 2019-04-19 Andrew MacFie

We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via…

Methodology · Statistics 2020-11-16 Alessandro Zito , Tommaso Rigon , Otso Ovaskainen , David Dunson

In this article, recent results about point processes are used in sampling theory. Precisely, we define and study a new class of sampling designs: determinantal sampling designs. The law of such designs is known, and there exists a simple…

Methodology · Statistics 2025-08-27 Vincent Loonis , Xavier Mary

We present an algebraic construction of trace-based De Bruijn tori over finite fields, focusing on the nonzero variant that omits the all-zero pattern. The construction arranges nonzero field elements on a toroidal grid using two…

Combinatorics · Mathematics 2025-06-25 Ming Hsuan Kang , Yu Hsuan Hsieh

We study the following combinatorial counting and sampling problems: can we efficiently sample from the Erd\H{o}s-R\'{e}nyi random graph $G(n,p)$ conditioned on triangle-freeness? Can we efficiently approximate the probability that $G(n,p)$…

Data Structures and Algorithms · Computer Science 2024-10-31 Matthew Jenssen , Will Perkins , Aditya Potukuchi , Michael Simkin
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