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High-dimensional systems that have a low-dimensional dominant behavior allow for model reduction and simplified analysis. We use differential analysis to formalize this important concept in a nonlinear setting. We show that dominance can be…

Systems and Control · Computer Science 2018-08-08 Fulvio Forni , Rodolphe Sepulchre

Humans recognize object structure from both their appearance and motion; often, motion helps to resolve ambiguities in object structure that arise when we observe object appearance only. There are particular scenarios, however, where…

Computer Vision and Pattern Recognition · Computer Science 2018-09-14 Tianfan Xue , Jiajun Wu , Zhoutong Zhang , Chengkai Zhang , Joshua B. Tenenbaum , William T. Freeman

Networks and graphs provide a simple but effective model to a vast set of systems which building blocks interact throughout pairwise interactions. Unfortunately, such models fail to describe all those systems which building blocks interact…

Physics and Society · Physics 2022-09-21 Mauro Faccin

We introduce a site-wise domination criterion for local percolation models, which enables the comparison of one-arm probabilities even in the absence of stochastic domination. The method relies on a local-to-global principle: if, at each…

We investigate higher-order Voronoi diagrams in the city metric. This metric is induced by quickest paths in the L1 metric in the presence of an accelerating transportation network of axis-parallel line segments. For the structural…

Computational Geometry · Computer Science 2012-04-20 Andreas Gemsa , D. T. Lee , Chih-Hung Liu , Dorothea Wagner

The spread of infectious disease in a human community or the proliferation of fake news on social media can be modeled as a randomly growing tree-shaped graph. The history of the random growth process is often unobserved but contains…

Probability · Mathematics 2021-01-15 Harry Crane , Min Xu

We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology. Persistent homology is a technique from topological data analysis that quantifies…

Cosmology and Nongalactic Astrophysics · Physics 2021-06-14 Matteo Biagetti , Alex Cole , Gary Shiu

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that…

Methodology · Statistics 2015-06-18 Brian P. Kent , Alessandro Rinaldo , Fang-Cheng Yeh , Timothy Verstynen

Understanding urban form is crucial for sustainable urban planning and enhancing quality of life. This study presents a data-driven framework to systematically identify and compare urban typologies across geographically and culturally…

Computers and Society · Computer Science 2025-05-07 Arthur Carmès , Léo Catteau , Andrew Sonta , Arash Tavakoli

Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has…

Physics and Society · Physics 2010-09-17 Andrea Lancichinetti , Mikko Kivela , Jari Saramaki , Santo Fortunato

Model-free forecasting of the temporal evolution of chaotic systems is crucial but challenging. Existing solutions require hyperparameter tuning, significantly hindering their wider adoption. In this work, we introduce a tree-based approach…

Machine Learning · Computer Science 2025-07-04 Adam Giammarese , Kamal Rana , Erik M. Bollt , Nishant Malik

Structure identification in cosmological simulations plays an important role in analysing simulation outputs. The definition of these structures directly impacts the inferred properties derived from these simulations. This paper proposes a…

Astrophysics of Galaxies · Physics 2025-01-16 Robel Geda , Romain Teyssier

The description of the Internet topology is an important open problem, recently tackled with the introduction of scale-free networks. In this paper we focus on the topological and dynamical properties of real Internet maps in a three years…

Statistical Mechanics · Physics 2009-11-07 Romualdo Pastor-Satorras , Alexei Vazquez , Alessandro Vespignani

The spatial distribution of income shapes the structure and organisation of cities and its understanding has broad societal implications. Despite an abundant literature, many issues remain unclear. In particular, all definitions of…

Physics and Society · Physics 2016-06-22 Rémi Louf , Marc Barthelemy

We consider the well-studied pattern counting problem: given a permutation $\pi \in \mathbb{S}_n$ and an integer $k > 1$, count the number of order-isomorphic occurrences of every pattern $\tau \in \mathbb{S}_k$ in $\pi$. Our first result…

Data Structures and Algorithms · Computer Science 2024-07-09 Gal Beniamini , Nir Lavee

We investigate the statistics of trees grown from some initial tree by attaching links to preexisting vertices, with attachment probabilities depending only on the valence of these vertices. We consider the asymptotic mass distribution that…

Statistical Mechanics · Physics 2007-05-23 François David , Philippe Di Francesco , Emmanuel Guitter , Thordur Jonsson

Decision trees are widely used for non-linear modeling, as they capture interactions between predictors while producing inherently interpretable models. Despite their popularity, performing inference on the non-linear fit remains largely…

Methodology · Statistics 2026-04-14 Soham Bakshi , Snigdha Panigrahi

Easy and intuitive navigability is of central importance in cities. The actual scale-free networking of urban street networks in their topological space, where navigation information is encoded by mapping roads to nodes and junctions to…

Physics and Society · Physics 2019-10-03 Jerome Benoit , Saif Eddin Jabari

Staged trees are a relatively recent class of probabilistic graphical models that extend Bayesian networks to formally and graphically account for non-symmetric patterns of dependence. Machine learning algorithms to learn them from data…

Applications · Statistics 2024-01-04 Manuele Leonelli , Gherardo Varando

We study the probabilistic behavior of persistence-based statistics and propose a novel nonparametric framework for detecting structural changes in high-dimensional random point clouds. We establish moment bounds and tightness results for…

Statistics Theory · Mathematics 2025-12-30 Toshiyuki Nakayama
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