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Framed combinatorial topology is a novel theory describing combinatorial phenomena arising at the intersection of stratified topology, singularity theory, and higher algebra. The theory synthesizes elements of classical combinatorial…

Geometric Topology · Mathematics 2021-12-30 Christoph Dorn , Christopher L. Douglas

The fragmentation processes of exchangeable partitions have already been studied by several authors. In this paper, we examine rather fragmentation of exchangeable compositions, that means partitions of $\mathbb{N}$ where the order of the…

Probability · Mathematics 2007-05-23 Anne-Laure Basdevant

The internal representations learned by deep networks are often sensitive to architecture-specific choices, raising questions about the stability, alignment, and transferability of learned structure across models. In this paper, we…

Machine Learning · Computer Science 2025-08-06 Saleh Nikooroo , Thomas Engel

Persistent homology, a technique from computational topology, has recently shown strong empirical performance in the context of graph classification. Being able to capture long range graph properties via higher-order topological features,…

Machine Learning · Computer Science 2024-12-20 Rubén Ballester , Bastian Rieck

The preservation of stochastic orders by distortion functions has become a topic of increasing interest in the reliability analysis of coherent systems. The reason of this interest is that the reliability function of a coherent system with…

Applications · Statistics 2024-09-30 Antonio Arriaza , Miguel Angel Sordo

We develop a theory to measure the variance and covariance of probability distributions defined on the nodes of a graph, which takes into account the distance between nodes. Our approach generalizes the usual (co)variance to the setting of…

Physics and Society · Physics 2021-08-19 Karel Devriendt , Samuel Martin-Gutierrez , Renaud Lambiotte

We consider inference for high-dimensional separately and jointly exchangeable arrays where the dimensions may be much larger than the sample sizes. For both exchangeable arrays, we first derive high-dimensional central limit theorems over…

Econometrics · Economics 2021-07-13 Harold D. Chiang , Kengo Kato , Yuya Sasaki

We study models of weighted exponential random graphs in the large network limit. These models have recently been proposed to model weighted network data arising from a host of applications including socio-econometric data such as migration…

Probability · Mathematics 2018-07-12 Shankar Bhamidi , Suman Chakraborty , Skyler Cranmer , Bruce Desmarais

Random embeddings project high-dimensional spaces to low-dimensional ones; they are careful constructions which allow the approximate preservation of key properties, such as the pair-wise distances between points. Often in the field of…

Optimization and Control · Mathematics 2022-06-08 Zhen Shao

In this paper we focus on the study of the monotonicity properties of the residual and the past extropy as well as on some characterization problems. We then apply the derived results to analyze further stochastic aspects of order…

Statistics Theory · Mathematics 2024-06-24 Mohamed Kayid

Different types of two- and three-dimensional representations of a finite metric space are studied that focus on the accurate representation of the linear order among the distances rather than their actual values. Lower and upper bounds for…

Combinatorics · Mathematics 2007-05-23 Jobst Heitzig

We introduce a class of random graphs that we argue meets many of the desiderata one would demand of a model to serve as the foundation for a statistical analysis of real-world networks. The class of random graphs is defined by a…

Statistics Theory · Mathematics 2015-12-11 Victor Veitch , Daniel M. Roy

The exchange algorithm is one of the most popular extensions of the Metropolis--Hastings algorithm to sample from doubly-intractable distributions. However, the theoretical exploration of the exchange algorithm is very limited. For example,…

Computation · Statistics 2021-08-20 Guanyang Wang

We characterize some asymptotic properties of edge exchangeable random graphs in terms of the measure used to generate them. In particular, we give a necessary and sufficient condition for eventual forever connectedness, a sufficient…

Probability · Mathematics 2026-05-07 Edward Eriksson

Statistical network modeling has focused on representing the graph as a discrete structure, namely the adjacency matrix, and considering the exchangeability of this array. In such cases, the Aldous-Hoover representation theorem (Aldous,…

Methodology · Statistics 2025-02-06 François Caron , Emily B. Fox

We introduce two new bootstraps for exchangeable random graphs. One, the "empirical graphon bootstrap", is based purely on resampling, while the other, the "histogram bootstrap", is a model-based "sieve" bootstrap. We show that both of them…

Methodology · Statistics 2025-01-07 Alden Green , Cosma Rohilla Shalizi

Maximum-entropy distributions are shown to appear in the probability calculus as approximations of a model by exchangeability or a model by sufficiency, the former model being preferable. The implications of this fact are discussed,…

Data Analysis, Statistics and Probability · Physics 2017-06-27 P. G. L. Porta Mana

Many natural patterns and shapes, such as meandering coastlines, clouds, or turbulent flows, exhibit a characteristic complexity mathematically described by fractal geometry. In recent years, the engineering of self-similar structures in…

Population structure can be modelled by evolutionary graphs, which can have a substantial, but very subtle influence on the fate of the arising mutants. Individuals are located on the nodes of these graphs, competing with each other to…

Populations and Evolution · Quantitative Biology 2018-10-31 Marius Möller , Laura Hindersin , Arne Traulsen

Quantifying the similarity between two mathematical structures or datasets constitutes a particularly interesting and useful operation in several theoretical and applied problems. Aimed at this specific objective, the Jaccard index has been…

Machine Learning · Computer Science 2021-11-19 Luciano da F. Costa