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Similarity is a fundamental measure in network analyses and machine learning algorithms, with wide applications ranging from personalized recommendation to socio-economic dynamics. We argue that an effective similarity measurement should…

Physics and Society · Physics 2015-12-07 Jian-Guo Liu , Lei Hou , Xue Pan , Qiang Guo , Tao Zhou

Score matching is an estimation procedure that has been developed for statistical models whose probability density function is known up to proportionality but whose normalizing constant is intractable, so that maximum likelihood is…

Methodology · Statistics 2024-04-23 Jiazhen Xu , Janice L. Scealy , Andrew T. A. Wood , Tao Zou

"Oscillations" occur in quite different kinds of many-particle-systems when two groups of particles with different directions of motion meet or intersect at a certain spot. We present a model of pedestrian motion that is able to reproduce…

Statistical Mechanics · Physics 2014-02-10 Tobias Kretz , Marko Woelki , Michael Schreckenberg

Calibration is a classical notion from the forecasting literature which aims to address the question: how should predicted probabilities be interpreted? In a world where we only get to observe (discrete) outcomes, how should we evaluate a…

Machine Learning · Computer Science 2025-09-03 Parikshit Gopalan , Lunjia Hu

Under the formalism of annealed averaging of the partition function, two types of random multifractal measures with their probability of multipliers satisfying power distribution and triangular distribution are investigated mathematically.…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Wei-Xing Zhou , Hai-Feng Liu , Zun-Hong Yu

Politically divided societies are also often divided emotionally: people like and trust those with similar political views (in-group favoritism) while disliking and distrusting those with different views (out-group animosity). This…

Social and Information Networks · Computer Science 2025-04-11 Buddhika Nettasinghe , Allon G. Percus , Kristina Lerman

A class of distance measures on probabilities -- the integral probability metrics (IPMs) -- is addressed: these include the Wasserstein distance, Dudley metric, and Maximum Mean Discrepancy. IPMs have thus far mostly been used in more…

Information Theory · Computer Science 2009-10-13 Bharath K. Sriperumbudur , Kenji Fukumizu , Arthur Gretton , Bernhard Schölkopf , Gert R. G. Lanckriet

Given the increasing popularity of algorithms for overlapping clustering, in particular in social network analysis, quantitative measures are needed to measure the accuracy of a method. Given a set of true clusters, and the set of clusters…

Physics and Society · Physics 2013-08-05 Aaron F. McDaid , Derek Greene , Neil Hurley

We introduce a simple, geometric model of opinion polarization. It is a model of political persuasion, as well as marketing and advertising, utilizing social values. It focuses on the interplay between different topics and persuasion…

Social and Information Networks · Computer Science 2021-08-26 Jan Hązła , Yan Jin , Elchanan Mossel , Govind Ramnarayan

We propose a new concept of codivergence, which quantifies the similarity between two probability measures $P_1, P_2$ relative to a reference probability measure $P_0$. In the neighborhood of the reference measure $P_0$, a codivergence…

Statistics Theory · Mathematics 2024-05-10 Alexis Derumigny , Johannes Schmidt-Hieber

The Poisson-Nernst-Planck system of equations used to model ionic transport is interpreted as a gradient flow for the Wasserstein distance and a free energy in the space of probability measures with finite second moment. A variational…

Analysis of PDEs · Mathematics 2015-09-08 David Kinderlehrer , Léonard Monsaingeon , Xiang Xu

Comparing the top $k$ elements between two or more ranked results is a common task in many contexts and settings. A few measures have been proposed to compare top $k$ lists with attractive mathematical properties, but they face a number of…

Information Theory · Computer Science 2013-10-02 Arun Konagurthu , James Collier

Polarization phenomena are essential for the understanding of elementary processes, and are typically large in the threshold region. The selection rules with respect to P-parity, angular momentum, isotopic spin and the Pauli principle allow…

Nuclear Theory · Physics 2007-05-23 Michail P. Rekalo , Egle Tomasi-Gustafsson

In this paper, we present a local information theoretic approach to explicitly learn probabilistic clustering of a discrete random variable. Our formulation yields a convex maximization problem for which it is NP-hard to find the global…

Machine Learning · Computer Science 2018-10-12 David Qiu , Anuran Makur , Lizhong Zheng

We derive an expression for the local transverse polarization of a boost-invariant expanding system of massive particles, which involves a set of dynamical spin moments. Starting from spin kinetic theory, we obtain a closed set of equations…

High Energy Physics - Phenomenology · Physics 2023-12-12 Nora Weickgenannt , Jean-Paul Blaizot

In general, gradient estimates are very important and necessary for deriving convergence results in different geometric flows, and most of them are obtained by analytic methods. In this paper, we will apply a stochastic approach to…

Differential Geometry · Mathematics 2015-01-14 Xin Chen , Li-Juan Cheng , Jing Mao

Clustering is the technique to partition data according to their characteristics. Data that are similar in nature belong to the same cluster [1]. There are two types of evaluation methods to evaluate clustering quality. One is an external…

Machine Learning · Computer Science 2024-09-05 Anupriya Vysala , Joseph Gomes

Pulsar radio emission is modelled as a sum of two completely polarized non-orthogonal modes with the randomly varying Stokes parameters and intensity ratio. The modes are the result of polarization evolution of the original natural waves in…

Astrophysics · Physics 2009-11-11 S. A. Petrova

Conley indices and Morse decompositions of flows can be found by using algorithms which rigorously analyze discrete dynamical systems. This usually involves integrating a time discretization of the flow using interval arithmetic. We compare…

Dynamical Systems · Mathematics 2015-11-16 Konstantin Mischaikow , Marian Mrozek , Frank Weilandt

Concentration of measure is a phenomenon in which a random variable that depends in a smooth way on a large number of independent random variables is essentially constant. The random variable will "concentrate" around its median or…

Probability · Mathematics 2015-08-25 Meg Walters
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