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Statistical laws describe regular patterns observed in diverse scientific domains, ranging from the magnitude of earthquakes (Gutenberg-Richter law) and metabolic rates in organisms (Kleiber's law), to the frequency distribution of words in…

Physics and Society · Physics 2025-02-14 Eduardo G. Altmann

Many living and non-living complex systems can be modeled and understood as collective systems made of heterogeneous components that self-organize and generate nontrivial morphological structures and behaviors. This chapter presents a brief…

Adaptation and Self-Organizing Systems · Physics 2018-01-09 Hiroki Sayama

In this paper, we consider the problem of exploring structural regularities of networks by dividing the nodes of a network into groups such that the members of each group have similar patterns of connections to other groups. Specifically,…

Physics and Society · Physics 2015-05-30 Hua-Wei Shen , Xue-Qi Cheng , Jia-Feng Guo

Jamming is a phenomenon shared by a wide variety of systems, such as granular materials, foams, and glasses in their high density regime. This has motivated the development of a theoretical framework capable of explaining many of their…

Statistical Mechanics · Physics 2021-06-24 Rafael Díaz Hernández Rojas , Giorgio Parisi , Federico Ricci-Tersenghi

This paper considers the joint distribution of elements of a random sample and an order statistic of the same sample. \ The motivation for this work stems from the important problem in reliability analysis, to estimate the number of…

Statistics Theory · Mathematics 2019-03-04 Ismihan Bairamov

Different models of random walks on the dual graphs of compact urban structures are considered. Analysis of access times between streets helps to detect the city modularity. The statistical mechanics approach to the ensembles of lazy random…

Physics and Society · Physics 2013-05-29 D. Volchenkov , Ph. Blanchard

The lack of specifications is a key difference between traditional software engineering and machine learning. We discuss how it drastically impacts how we think about divide-and-conquer approaches to system design, and how it impacts reuse,…

Software Engineering · Computer Science 2021-05-14 Christian Kästner , Eunsuk Kang , Sven Apel

We numerically analyze the statistical properties of complex system with conditions subjecting the matrix elements to a set of specific constraints besides symmetry, resulting in various structures in their matrix representation. Our…

Disordered Systems and Neural Networks · Physics 2019-02-20 Triparna Mondal , Pragya Shukla

Structural causal models describe how the components of a robotic system interact. They provide both structural and functional information about the relationships that are present in the system. The structural information outlines the…

Robotics · Computer Science 2025-08-12 Alejandro Murillo-Gonzalez , Junhong Xu , Lantao Liu

Complex macroscopic behaviour can arise in many-body systems with only very simple elements as a consequence of the combination of competition and inhomogeneity. This paper attempts to illustrate how statistical physics has driven this…

Disordered Systems and Neural Networks · Physics 2012-01-10 David Sherrington

We discuss the problem of counting certain LEGO structures, primarily those comprising parallel $w \times 1$ tiles. These can be combined, as a single LEGO structure, by interlocking the tiles. %Alternatively, if the interlocking condition…

Combinatorics · Mathematics 2026-05-11 Anthony J Guttmann , Rasmus M Nilsson

A widely recognized organizing principle of networks is structural homophily, which suggests that people with more common neighbors are more likely to connect with each other. However, what influence the diverse structures embedded in…

Social and Information Networks · Computer Science 2017-10-06 Yuxiao Dong , Reid A. Johnson , Jian Xu , Nitesh V. Chawla

Many complex systems satisfy a set of constraints on their degrees of freedom, and at the same time, they are able to work and adapt to different conditions. Here, we describe the emergence of this ability in a simplified model in which the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Ginestra Bianconi , Roberto Mulet

Coding information is the main source of heterogeneity (non-randomness) in the sequences of bacterial genomes. This information can be naturally modeled by analysing cluster structures in the "in-phase" triplet distributions of relatively…

Genomics · Quantitative Biology 2011-11-09 A. N. Gorban , T. G. Popova , A. Yu. Zinovyev

The design space for a self-assembled multicomponent objects ranges from a solution in which every building block is unique to one with the minimum number of distinct building blocks that unambiguously define the target structure. Using a…

Soft Condensed Matter · Physics 2023-03-13 Joakim Bohlin , Andrew J. Turberfield , Ard A. Louis , Petr Šulc

Inference problems with conjectured statistical-computational gaps are ubiquitous throughout modern statistics, computer science and statistical physics. While there has been success evidencing these gaps from the failure of restricted…

Computational Complexity · Computer Science 2020-06-30 Matthew Brennan , Guy Bresler

Statistical tasks such as density estimation and approximate Bayesian inference often involve densities with unknown normalising constants. Score-based methods, including score matching, are popular techniques as they are free of…

Machine Learning · Statistics 2021-12-22 Li K. Wenliang , Heishiro Kanagawa

Assembly planning is a difficult problem for companies. Many disciplines such as design, planning, scheduling, and manufacturing execution need to be carefully engineered and coordinated to create successful product assembly plans. Recent…

Robotics · Computer Science 2020-05-13 Jade Master , Evan Patterson , Shahin Yousfi , Arquimedes Canedo

This paper describes a compound Poisson-based random effects structure for modeling zero-inflated data. Data with large proportion of zeros are found in many fields of applied statistics, for example in ecology when trying to model and…

Applications · Statistics 2009-07-29 Marie-Pierre Etienne , Eric Parent , Benoit Hugues , Bernier Jacques

The inference of causal relationships using observational data from partially observed multivariate systems with hidden variables is a fundamental question in many scientific domains. Methods extracting causal information from conditional…

Machine Learning · Statistics 2020-10-13 Daniel Chicharro , Michel Besserve , Stefano Panzeri