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Related papers: Structure and randomness in combinatorics

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Insightful interdisciplinary collaboration is essential to the principled governance of technology. When such efforts address the interaction between computation and society, they often focus on modeling, the process by which computer…

Computers and Society · Computer Science 2025-05-29 Samuel Judson , Joan Feigenbaum

Approximations of functions with finite data often do not respect certain "structural" properties of the functions. For example, if a given function is non-negative, a polynomial approximation of the function is not necessarily also…

Numerical Analysis · Mathematics 2020-08-20 Vidhi Zala , Robert M. Kirby , Akil Narayan

Is there a characteristic of coordination languages that makes them qualitatively different from general programming languages and deserves special academic attention? This report proposes a nuanced answer in three parts. The first part…

Software Engineering · Computer Science 2013-06-17 Raphael 'kena' Poss

The science of complexity is far from being fully understood and even its foundations are not well established. On the other hand, during the last decade, the random motion of particles or waves - the so-called diffusion - has been known…

Statistical Mechanics · Physics 2009-08-14 Guilherme R. Rezende , Luciano C. Lapas , Fernando A. Oliveira

Classical random matrix ensembles were originally introduced in physics to approximate quantum many-particle nuclear interactions. However, there exists a plethora of quantum systems whose dynamics is explained in terms of few-particle…

Quantum Physics · Physics 2021-11-17 Manan Vyas , Thomas H. Seligman

Entangled multipartite states are resources for universal quantum computation, but they can also give rise to ensembles of unitary transformations, a topic usually studied in the context of random quantum circuits. Using several graph state…

Quantum Physics · Physics 2016-05-25 Peter S. Turner , Damian Markham

We give a decomposition of the posterior predictive variance using the law of total variance and conditioning on a finite dimensional discrete random variable. This random variable summarizes various features of modeling that are used to…

Methodology · Statistics 2022-09-02 Dean Dustin , Bertrand Clarke

In this article we demonstrate how algorithmic probability theory is applied to situations that involve uncertainty. When people are unsure of their model of reality, then the outcome they observe will cause them to update their beliefs. We…

Artificial Intelligence · Computer Science 2014-05-26 Phil Maguire , Philippe Moser , Rebecca Maguire , Mark Keane

Matching logic is a logical framework for specifying and reasoning about programs using pattern matching semantics. A pattern is made up of a number of structural components and constraints. Structural components are syntactically matched,…

Logic in Computer Science · Computer Science 2024-11-01 Ádám Kurucz , Péter Bereczky , Dániel Horpácsi

The information in an individual finite object (like a binary string) is commonly measured by its Kolmogorov complexity. One can divide that information into two parts: the information accounting for the useful regularity present in the…

Computational Complexity · Computer Science 2007-05-23 Paul Vitanyi

Ensembling is a simple and popular technique for boosting evaluation performance by training multiple models (e.g., with different initializations) and aggregating their predictions. This approach is commonly reserved for the largest…

Machine Learning · Computer Science 2020-05-05 Dan Kondratyuk , Mingxing Tan , Matthew Brown , Boqing Gong

Defects, and in particular topological defects, are architectural motifs that play a crucial role in natural materials. Here we provide a systematic strategy to introduce such defects in mechanical metamaterials. We first present…

Soft Condensed Matter · Physics 2020-03-18 Anne S. Meeussen , Erdal C. Oguz , Yair Shokef , Martin van Hecke

This essay advocates the view that any problem that has a meaningful empirical content, can be formulated in constructive, more definitely, finite terms. We consider combinatorial models of dynamical systems and approaches to statistical…

Quantum Physics · Physics 2015-07-21 Vladimir V. Kornyak

We describe a method for utilizing the known structure of input data to make learning more efficient. Our work is in the domain of programming languages, and we use deep neural networks to do program analysis. Computer programs include a…

Neural and Evolutionary Computing · Computer Science 2019-04-01 Zehra Sura , Tong Chen , Hyojin Sung

It is shown that an ensemble of particles with tripolar (colour) charges will necessarily cohere in a hierarchy of structures, from simple clusters and strings to complex aggregates and cyclic molecule-like structures. The basic…

General Physics · Physics 2007-05-23 V. N. Yershov

Self-assembly materials are traditionally designed so that molecular or meso-scale components form a single kind of large structure. Here, we propose a scheme to create "multifarious assembly mixtures", which self-assemble many different…

Disordered Systems and Neural Networks · Physics 2015-06-22 Arvind Murugan , Zorana Zeravcic , Michael P. Brenner , Stanislas Leibler

To analyze the evolutionary emergence of structural complexity in physical processes we introduce a general, but tractable, model of objects that interact to produce new objects. Since the objects--\emph{$epsilon$-machines}--have well…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 James P. Crutchfield , Olof Gornerup

This is a survey of recent developments in combinatorics. The goal is to give a big picture of its many interactions with other areas of mathematics, such as: group theory, representation theory, commutative algebra, geometry (including…

Combinatorics · Mathematics 2015-03-17 Cristian Lenart

Clustering attempts to partition data instances into several distinctive groups, while the similarities among data belonging to the common partition can be principally reserved. Furthermore, incomplete data frequently occurs in many…

Machine Learning · Computer Science 2022-08-30 Miao Cheng , Xinge You

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
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