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We study the problem of approximating a discrete probability distribution, such as the next-token distribution of a large language model, by a dyadic distribution induced by a binary tree under encoding rate constraints. The objective is to…

Information Theory · Computer Science 2026-05-08 Daniella Bar-Lev , Farzad Farnoud , Ryan Gabrys

Rotation distances measure the differences in structure between rooted ordered binary trees. The one-dimensional skeleta of associahedra are rotation graphs, where two vertices representing trees are connected by an edge if they differ by a…

Data Structures and Algorithms · Computer Science 2020-06-29 Sean Cleary , Haris Nadeem

We view the folding of RNA-sequences as a map that assigns a pattern of base pairings to each sequence, known as secondary structure. These preimages can be constructed as random graphs (i.e. the neutral networks associated to the structure…

adap-org · Physics 2008-02-03 Christian V. Forst , Christian Reidys , Jacqueline Weber

For fitness preferential attachment random networks, we define the empirical degree and pair measure, which counts the number of vertices of a given degree and the number of edges with given fits, and the sample path empirical degree…

Information Theory · Computer Science 2014-06-13 K. Doku-Amponsah , F. O. Mettle , T. Narh-Ansah

In this article, we study random graphs with a given degree sequence $d_1, d_2, \cdots, d_n$ from the configuration model. We show that under mild assumptions of the degree sequence, the spectral distribution of the normalized Laplacian…

Probability · Mathematics 2024-12-04 Shuyi Wang , Kevin Li , Jiaoyang Huang

Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying tree structure, given only observations of its terminal…

Machine Learning · Statistics 2021-12-08 Yariv Aizenbud , Ariel Jaffe , Meng Wang , Amber Hu , Noah Amsel , Boaz Nadler , Joseph T. Chang , Yuval Kluger

For an arbitrary negative Schwarzian unimodal map with non-flat critical point, we establish the level-2 Large Deviation Principle (LDP) for empirical distributions. We also give an example of a multimodal map for which the level-2 LDP does…

Dynamical Systems · Mathematics 2026-03-18 Hiroki Takahasi , Masato Tsujii

We study a variant of the standard random intersection graph model ($G(n,m,F,H)$) in which random weights are assigned to both vertex types in the bipartite structure. Under certain assumptions on the distributions of these weights, the…

Combinatorics · Mathematics 2010-03-10 Yilun Shang

We consider real-valued branching random walks and prove a large deviation result for the position of the rightmost particle. The position of the rightmost particle is the maximum of a collection of a random number of dependent random…

Probability · Mathematics 2019-06-27 Nina Gantert , Thomas Höfelsauer

We define a class of properties on random plane trees, which we call subtree additive properties, inspired by the combinatorics of certain biologically-interesting properties in a plane tree model of RNA secondary structure. The class of…

Combinatorics · Mathematics 2021-01-15 Anna Kirkpatrick , Chidozie Onyeze

In a one-parameter model for evolution of random trees, which also includes the Barabasi-Albert random tree, almost sure behavior and the limiting distribution of the degree of a vertex in a fixed position are examined. Results about Polya…

Probability · Mathematics 2010-07-27 Agnes Backhausz

We consider distributed networks, such as peer-to-peer networks, whose structure can be manipulated by adjusting the rules by which vertices enter and leave the network. We focus in particular on degree distributions and show that, with…

Physics and Society · Physics 2007-10-18 Gourab Ghoshal , M. E. J. Newman

We extend recent methods for parametric sequence alignment to the parameter space for scoring RNA folds. This involves the construction of an RNA polytope. A vertex of this polytope corresponds to RNA secondary structures with common…

Biomolecules · Quantitative Biology 2009-04-24 Valerie Hower , Christine E. Heitsch

Our work is concerned with the generation and targeted design of RNA, a type of genetic macromolecule that can adopt complex structures which influence their cellular activities and functions. The design of large scale and complex…

Biomolecules · Quantitative Biology 2021-02-02 Zichao Yan , William L. Hamilton , Mathieu Blanchette

We propose a general approach to the description of spectra of complex networks. For the spectra of networks with uncorrelated vertices (and a local tree-like structure), exact equations are derived. These equations are generalized to the…

Statistical Mechanics · Physics 2009-11-10 S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes , A. N. Samukhin

Random critical branching trees (CBTs) are generated by the multiplicative branching process, where the branching number is determined stochastically, independent of the degree of their ancestor. Here we show analytically that despite this…

Statistical Mechanics · Physics 2015-05-13 J. S. Kim , B. Kahng , D. Kim

We prove the large deviation principle (LDP) for posterior distributions arising from subfamilies of full exponential families, allowing misspecification of the model. Moreover, motivated by the so-called inverse Sanov Theorem (see e.g.…

Statistics Theory · Mathematics 2022-06-17 Claudio Macci , Mauro Piccioni

This paper extends the study of fringe trees in random plane trees with a given degree statistic. While previous work established the asymptotic normality of the count of fringe trees isomorphic to a fixed tree, we investigate the case…

Probability · Mathematics 2026-04-08 Gabriel Berzunza Ojeda , Cecilia Holmgren , Svante Janson

We study the size of the largest biconnected components in sparse Erd\H{o}s-R\'enyi graphs with finite connectivity and Barab\'asi-Albert graphs with non-integer mean degree. Using a statistical-mechanics inspired Monte Carlo approach we…

Disordered Systems and Neural Networks · Physics 2019-04-05 Hendrik Schawe , Alexander K. Hartmann

We analyze numerical properties of Layer-wise relevance propagation (LRP)-type attribution methods by representing them as a product of modified gradient matrices. This representation creates an analogy to matrix multiplications of…

Machine Learning · Computer Science 2025-09-12 Alexander Binder , Nastaran Takmil-Homayouni , Urun Dogan
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