48 citations · 165 across the 24 of their papers we have counts for
26 papers
Some enumerative properties of parking functions
Richard P. Stanley, Mei Yin
A parking function is a sequence of positive integers such that if is the increasing rearrangement of , then f…
Permutation Statistics in Conjugacy Classes of the Symmetric Group
Jesse Campion Loth, Michael Levet, Kevin Liu +3
We introduce the notion of a weighted inversion statistic on the symmetric group, and examine its distribution on each conjugacy class. Our work generalizes the study of several co…
Odd Covers of Graphs
Calum Buchanan, Alexander Clifton, Eric Culver +4
Given a finite simple graph , an odd cover of is a collection of complete bipartite graphs, or bicliques, in which each edge of appears in an odd number of bicliques and…
Parking functions, multi-shuffle, and asymptotic phenomena
Mei Yin
Given a positive-integer-valued vector with . A -parking function of length is a sequence of positive integers wh…
Parking functions: Interdisciplinary connections
Mei Yin
Suppose that drivers each choose a preferred parking space in a linear car park with spots. In order, each driver goes to their chosen spot and parks there if possible, and…
Parking functions: From combinatorics to probability
Richard Kenyon, Mei Yin
Suppose that drivers each choose a preferred parking space in a linear car park with spots. In order, each driver goes to their chosen spot and parks there if possible, and…
Remarks on power-law random graphs
Mei Yin
The theory of graphons is an important tool in understanding properties of large networks. We investigate a power-law random graph model and cast it in the graphon framework. The d…
Interval parking functions
Emma Colaric, Ryan DeMuse, Jeremy L. Martin +1
Interval parking functions (IPFs) are a generalization of ordinary parking functions in which each car is willing to park only in a fixed interval of spaces. Each interval parking…
Dimension reduction in vertex-weighted exponential random graphs
Ryan DeMuse, Mei Yin
We investigate the behavior of vertex-weighted exponential random graphs. We show that vertex-weighted exponential random graphs with edge weights induced by products of independen…
Mixing Time of Vertex-Weighted Exponential Random Graphs
Ryan DeMuse, Terry Easlick, Mei Yin
Exponential random graph models have become increasingly important in the study of modern networks ranging from social networks, economic networks, to biological networks. They see…
Ground States for Exponential Random Graphs
Rajinder Mavi, Mei Yin
We propose a perturbative method to estimate the normalization constant in exponential random graph models as the weighting parameters approach infinity. As an application, we give…
Phase Transitions in Edge-Weighted Exponential Random Graphs: Near-Degeneracy and Universality
Ryan DeMuse, Danielle Larcomb, Mei Yin
Conventionally used exponential random graphs cannot directly model weighted networks as the underlying probability space consists of simple graphs only. Since many substantively i…
Phase transitions in edge-weighted exponential random graphs
Mei Yin
The exponential family of random graphs represents an important and challenging class of network models. Despite their flexibility, conventionally used exponential random graphs ha…
A detailed investigation into near degenerate exponential random graphs
Mei Yin
The exponential family of random graphs has been a topic of continued research interest. Despite the relative simplicity, these models capture a variety of interesting features dis…
Large deviations and exact asymptotics for constrained exponential random graphs
Mei Yin
We present a technique for approximating generic normalization constants subject to constraints. The method is then applied to derive the exact asymptotics for the conditional norm…
Reciprocity in directed networks
Mei Yin, Lingjiong Zhu
Reciprocity is an important characteristic of directed networks and has been widely used in the modeling of World Wide Web, email, social, and other complex networks. In this paper…
Asymptotics for Sparse Exponential Random Graph Models
Mei Yin, Lingjiong Zhu
We study the asymptotics for sparse exponential random graph models where the parameters may depend on the number of vertices of the graph. We obtain exact estimates for the mean a…
On the asymptotics of constrained exponential random graphs
Richard Kenyon, Mei Yin
The unconstrained exponential family of random graphs assumes no prior knowledge of the graph before sampling, but it is natural to consider situations where partial information ab…
Asymptotic quantization of exponential random graphs
Mei Yin, Alessandro Rinaldo, Sukhada Fadnavis
We describe the asymptotic properties of the edge-triangle exponential random graph model as the natural parameters diverge along straight lines. We show that as we continuously va…
Critical phenomena in exponential random graphs
Mei Yin
The exponential family of random graphs is one of the most promising class of network models. Dependence between the random edges is defined through certain finite subgraphs, analo…
A Markov chain approach to renormalization group transformations
Mei Yin
We aim at an explicit characterization of the renormalized Hamiltonian after decimation transformation of a one-dimensional Ising-type Hamiltonian with a nearest-neighbor interacti…
A cluster expansion approach to exponential random graph models
Mei Yin
The exponential family of random graphs is among the most widely-studied network models. We show that any exponential random graph model may alternatively be viewed as a lattice ga…
Renormalization Group Transformations Near the Critical Point: Some Rigorous Results
Mei Yin
We consider renormalization group (RG) transformations for classical Ising-type lattice spin systems in the infinite volume limit. Formally, the RG maps a Hamiltonian H into a reno…
Phase transitions in exponential random graphs
Charles Radin, Mei Yin
We derive the full phase diagram for a large family of two-parameter exponential random graph models, each containing a first order transition curve ending in a critical point.