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Related papers: Parametrization of Symmetry in Data

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Statistical models that possess symmetry arise in diverse settings such as random fields associated to geophysical phenomena, exchangeable processes in Bayesian statistics, and cyclostationary processes in engineering. We formalize the…

Statistics Theory · Mathematics 2011-12-01 Parikshit Shah , Venkat Chandrasekaran

We examine the interplay of symmetry and topological order in $2+1$ dimensional topological phases of matter. We present a definition of the \it topological symmetry \rm group, which characterizes the symmetry of the emergent topological…

Strongly Correlated Electrons · Physics 2019-10-16 Maissam Barkeshli , Parsa Bonderson , Meng Cheng , Zhenghan Wang

Symmetry principles underlie and guide scientific theory and research, from Curie's invariance formulation to modern applications across physics, chemistry, and mathematics. Building on a recent matrix Lie group measurement model, this…

Methodology · Statistics 2025-12-19 William R. Nugent

Methods for the design of physical parameterization schemes that possess certain invariance properties are discussed. These methods are based on different techniques of group classification and provide means to determine expressions for…

Mathematical Physics · Physics 2013-01-04 Roman O. Popovych , Alexander Bihlo

Multiparameter persistent homology has emerged as a powerful generalization of topological data analysis, capable of encoding multivariate filtrations. However, the algebraic complexity of multiparameter persistence modules, marked by wild…

Algebraic Topology · Mathematics 2026-04-14 Mauricio Angel

Modeling symmetry breaking is essential for understanding the fundamental changes in the behaviors and properties of physical systems, from microscopic particle interactions to macroscopic phenomena like fluid dynamics and cosmic…

Machine Learning · Computer Science 2025-07-11 Rui Wang , Elyssa Hofgard , Han Gao , Robin Walters , Tess E. Smidt

Symmetry arguments are frequently used -- often implicitly -- in mathematical modeling of natural selection. Symmetry simplifies the analysis of models and reduces the number of distinct population states to be considered. Here, I introduce…

Populations and Evolution · Quantitative Biology 2023-07-14 Benjamin Allen

Persistent homology is a popular and useful tool for analysing finite metric spaces, revealing features that can be used to distinguish sets of unlabeled points and as input into machine learning pipelines. The famous stability theorem of…

Computational Geometry · Computer Science 2024-05-10 Philip Smith , Vitaliy Kurlin

Persistent homology, a central tool of topological data analysis, provides invariants of data called barcodes (also known as persistence diagrams). A barcode is simply a multiset of real intervals. Recent work of Edelsbrunner, Jablonski,…

Algebraic Topology · Mathematics 2020-10-12 Ulrich Bauer , Michael Lesnick

Many remarkably robust, rapid and spontaneous self-assembly phenomena in nature can be modeled geometrically starting from a collection of rigid bunches of spheres. This paper highlights the role of symmetry in sphere-based assembly…

Combinatorics · Mathematics 2016-03-15 Meera Sitharam , Andrew Vince , Menghan Wang , Miklos Bona

The concept of complexity appears in virtually all areas of knowledge. Its intuitive meaning shares similarities across fields, but disagreements between its details hinders a general definition, leading to a plethora of proposed…

Statistical Mechanics · Physics 2023-10-04 Roberto C. Alamino

Exploiting symmetry inherent in data can significantly improve the sample efficiency of a learning procedure and the generalization of learned models. When data clearly reveals underlying symmetry, leveraging this symmetry can naturally…

Machine Learning · Computer Science 2024-12-20 Gyeonghoon Ko , Hyunsu Kim , Juho Lee

We introduce group crosscoders, an extension of crosscoders that systematically discover and analyse symmetrical features in neural networks. While neural networks often develop equivariant representations without explicit architectural…

Machine Learning · Computer Science 2024-11-04 Liv Gorton

A symmetry is a `change without change'. As simple as it sounds, this concept is the fundamental cornerstone that unifies all branches of theoretical physics. Virtually all physical laws -- ranging from classical mechanics and…

Molecular Networks · Quantitative Biology 2025-03-25 Hernan A. Makse , Paolo Boldi , Francesco Sorrentino , Ian Stewart

Extraction of structure, in particular of group symmetries, is increasingly crucial to understanding and building intelligent models. In particular, some information-theoretic models of parsimonious learning have been argued to induce…

Information Theory · Computer Science 2025-07-08 Hippolyte Charvin , Nicola Catenacci Volpi , Daniel Polani

Symmetry is one of the most general and useful concepts in physics. A theory or a system that has a symmetry is fundamentally constrained by it. The same constraints do not apply when the symmetry is broken. The quantitative determination…

Quantum Physics · Physics 2019-01-23 Ivan Fernandez-Corbaton

The problem of detecting and quantifying the presence of symmetries in datasets is useful for model selection, generative modeling, and data analysis, amongst others. While existing methods for hard-coding transformations in neural networks…

Machine Learning · Computer Science 2023-07-06 Alex Gabel , Victoria Klein , Riccardo Valperga , Jeroen S. W. Lamb , Kevin Webster , Rick Quax , Efstratios Gavves

Finite group symmetry is commonplace in Physics, in particular through crystallographic groups occurring in condensed matter physics -- but also through the inversions (C,P,T and their combinations) occurring in high energy physics and…

Mathematical Physics · Physics 2008-03-26 G. Gaeta

Symmetry is an implicit objective in structural form-finding that often reconciles efficiency and aesthetics. This paper identifies the symmetry of polyhedral diagrams in three-dimensional graphic statics (3DGS) as point groups and…

Computational Geometry · Computer Science 2026-04-29 Yefan Zhi , Yao Lu , Masoud Akbarzadeh

A theory of modules over posets is developed to define computationally feasible, topologically interpretable data structures, in terms of birth and death of homology classes, for persistent homology with multiple real parameters. To replace…

Algebraic Topology · Mathematics 2020-08-13 Ezra Miller
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