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For any finite partially ordered set $P$, the $P$-Eulerian polynomial is the generating function for the descent number over the set of linear extensions of $P$, and is closely related to the order polynomial of $P$ arising in the theory of…

Combinatorics · Mathematics 2024-09-11 T. Kyle Petersen , Yan Zhuang

Trees or rooted trees have been generously studied in the literature. A forest is a set of trees or rooted trees. Here we give recurrence relations between the number of some kind of rooted forest with $k$ roots and that with $k+1$ roots on…

Combinatorics · Mathematics 2017-02-08 Song Guo , Victor J. W. Guo

A matching of the set $[2n]=\{ 1,2,\ldots ,2n\}$ is a partition of $[2n]$ into blocks with two elements, i.e. a graph on $[2n]$ such that every vertex has degree one. Given two matchings $\sigma$ and $\tau$ , we say that $\sigma$ is a…

Combinatorics · Mathematics 2020-09-03 Matteo Cervetti , Luca Ferrari

Most current computer vision datasets are composed of disconnected sets, such as images from different classes. We prove that distributions of this type of data cannot be represented with a continuous generative network without error. They…

Machine Learning · Computer Science 2020-06-26 Lorenzo Luzi , Randall Balestriero , Richard G. Baraniuk

A time series is a sequence of observations taken sequentially in time. The autoregressive integrated moving average is a class of the model more used for times series data. However, this class of model has two critical limitations. It fits…

Methodology · Statistics 2020-02-14 Renato Rodrigues Silva

In this work, we present the Grounded Recurrent Neural Network (GRNN), a recurrent neural network architecture for multi-label prediction which explicitly ties labels to specific dimensions of the recurrent hidden state (we call this…

Machine Learning · Statistics 2017-05-25 Ankit Vani , Yacine Jernite , David Sontag

Most of the successful deep neural network architectures are structured, often consisting of elements like convolutional neural networks and gated recurrent neural networks. Recently, graph neural networks have been successfully applied to…

Machine Learning · Computer Science 2019-06-04 Zhen Zhang , Fan Wu , Wee Sun Lee

This paper considers the enumeration of ternary trees (i.e. rooted ordered trees in which each vertex has 0 or 3 children) avoiding a contiguous ternary tree pattern. We begin by finding recurrence relations for several simple tree…

Combinatorics · Mathematics 2011-12-30 Nathan Gabriel , Katherine Peske , Lara Pudwell , Samuel Tay

Graph neural networks (GNNs) are a popular class of machine learning models whose major advantage is their ability to incorporate a sparse and discrete dependency structure between data points. Unfortunately, GNNs can only be used when such…

Machine Learning · Computer Science 2020-06-22 Luca Franceschi , Mathias Niepert , Massimiliano Pontil , Xiao He

We introduce and study the {\em orderly spanning trees} of plane graphs. This algorithmic tool generalizes {\em canonical orderings}, which exist only for triconnected plane graphs. Although not every plane graph admits an orderly spanning…

Data Structures and Algorithms · Computer Science 2015-02-06 Yi-Ting Chiang , Ching-Chi Lin , Hsueh-I Lu

A numerical semigroup is a subset of the non-negative integers that is closed under addition. For a randomly generated numerical semigroup, the expected number of minimum generators can be expressed in terms of a doubly-indexed sequence of…

Combinatorics · Mathematics 2018-09-27 Calvin Leng , Christopher O'Neill

We present a certain generalization of a recent result of M. I. Cirnu on linear recurrence relations with coefficient in progressions [2]. We provide some interesting examples related to some well-known integer sequences, such as Fibonacci…

Number Theory · Mathematics 2015-03-19 Jerico B. Bacani , Julius Fergy T. Rabago

We generalize the solution of linear recurrence relations from fields to central division algebras, adapting the standard tools of companion matrices and characteristic polynomials to the non-commutative setting. We then solve linear…

Rings and Algebras · Mathematics 2025-09-23 Adam Chapman , Solomon Vishkautsan

Common meadows are commutative and associative algebraic structures with two operations (addition and multiplication) with additive and multiplicative identities and for which inverses are total. The inverse of zero is an error term…

Rings and Algebras · Mathematics 2024-06-10 João Dias , Bruno Dinis

A derangement is a permutation with no fixed point, and a nonderangement is a permutation with at least one fixed point. There is a one-term recurrence for the number of derangements of $n$ elements, and we describe a bijective proof of…

Combinatorics · Mathematics 2023-09-11 Melanie Ferreri

The Guarded Fragment (GF) is a well-established decidable fragment of first-order logic. We study an extension of GF with nested equivalence relations, namely a family of distinguished binary predicates $E_1, E_2, \dots$ interpreted as…

Logic in Computer Science · Computer Science 2026-05-15 Oskar Fiuk

Fathi and Pageault have recently shown a connection between Auslander's generalized recurrent set $GR(f)$ and Easton's strong chain recurrent set. We study $GR(f)$ by examining that connection in more detail, as well as connections with…

Dynamical Systems · Mathematics 2016-07-13 Jim Wiseman

We formulate and prove a general recurrence relation that applies to integrals involving orthogonal polynomials and similar functions. A special case are connection coefficients between two sets of orthonormal polynomials, another example…

Classical Analysis and ODEs · Mathematics 2023-08-17 Jing Gao , Arieh Iserles

We establish multiple recurrence results for pretentious measure-preserving multiplicative actions along generalized Pythagorean triples, that is, solutions to the equation $ax^2 + b y^2 = c z^2$. This confirms the ergodic-theoretic form of…

Dynamical Systems · Mathematics 2025-08-26 Nikos Frantzikinakis , Andreas Mountakis

Generative Flow Networks (GFlowNets), a new family of probabilistic samplers, have recently emerged as a promising framework for learning stochastic policies that generate high-quality and diverse objects proportionally to their rewards.…

Machine Learning · Computer Science 2024-06-05 Chunhui Li , Cheng-Hao Liu , Dianbo Liu , Qingpeng Cai , Ling Pan
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