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This article proposes a new discrete framework for approximating solutions to shape optimization problems under convexity constraints. The numerical method, based on the support function or the gauge function, is guaranteed to generate…

Optimization and Control · Mathematics 2022-03-15 Beniamin Bogosel

This paper presents a unified geometric framework for the statistical analysis of a general ill-posed linear inverse model which includes as special cases noisy compressed sensing, sign vector recovery, trace regression, orthogonal matrix…

Statistics Theory · Mathematics 2020-07-27 T. Tony Cai , Tengyuan Liang , Alexander Rakhlin

Following recent developments in discrete gravity, we study geometrical variables (angles and forms) of simplices in the discrete geometry point of view. Some of our relatively new results include: new ways of writing a set of simplices…

General Relativity and Quantum Cosmology · Physics 2016-09-20 Seramika Ariwahjoedi , Jusak Sali Kosasih , Carlo Rovelli , Freddy P. Zen

A geometrical formulation for adjoint-symmetries as 1-forms is studied for general partial differential equations (PDEs), which provides a dual counterpart of the geometrical meaning of symmetries as tangent vector fields on the solution…

Mathematical Physics · Physics 2021-03-23 Stephen C. Anco , Bao Wang

In this paper, we propose the Fourier Discrepancy Function, a new discrepancy to compare discrete probability measures. We show that this discrepancy takes into account the geometry of the underlying space. We prove that the Fourier…

Machine Learning · Statistics 2021-11-19 Auricchio Gennaro , Codegoni Andrea , Gualandi Stefano , Zambon Lorenzo

We have established a coherent framework for applying variational methods to partial differential equations on hypergraphs, which includes the propositions of calculus and function spaces on hypergraphs. Several results related to the…

Analysis of PDEs · Mathematics 2024-04-01 Mengqiu Shao , Yulu Tian , Liang Zhao

Author developed a uniform model for different spaces where distance and angle measure kinds are parameters. This model is calculus centric, but can also be used in theoretical research. It is useful in the following domains: deduction of…

Metric Geometry · Mathematics 2018-07-30 Alexandru Popa

In this article we present pictorially the foundation of differential geometry which is a crucial tool for multiple areas of physics, notably general and special relativity, but also mechanics, thermodynamics and solving differential…

Differential Geometry · Mathematics 2017-09-26 Jonathan Gratus

Geometric quantiles are popular location functionals to build rank-based statistical procedures in multivariate settings. They are obtained through the minimization of a non-smooth convex objective function. As a result, the singularity of…

Statistics Theory · Mathematics 2026-02-11 Dimitri Konen , Gilles Stupfler

There exists a well established differential topological theory of singularities of ordinary differential equations. It has mainly studied scalar equations of low order. We propose an extension of the key concepts to arbitrary systems of…

Commutative Algebra · Mathematics 2021-03-12 Markus Lange-Hegermann , Daniel Robertz , Werner M. Seiler , Matthias Seiss

We present a self-contained analysis of theories of discrete 2D gravity coupled to matter, using geometric methods to derive equations for generating functions in terms of free (noncommuting) variables. For the class of discrete gravity…

High Energy Physics - Theory · Physics 2008-11-26 Sean M. Carroll , Miguel E. Ortiz , Washington Taylor

This paper presents a mathematical framework for analyzing machine learning models through the geometry of their induced partitions. By representing partitions as Riemannian simplicial complexes, we capture not only adjacency relationships…

Machine Learning · Computer Science 2025-08-05 Pawel Gajer , Jacques Ravel

Following our joint work arXiv:1003.4578 with Robert Langlands, we make the first steps toward developing geometric methods for analyzing trace formulas in the case of the function field of a curve defined over a finite field. We also…

Representation Theory · Mathematics 2015-03-17 Edward Frenkel , Ngo Bao Chau

Geometric algebra is an optimal frame work for calculating with vectors. The geometric algebra of a space includes elements that represent all the its subspaces (lines, planes, volumes, ...). Conformal geometric algebra expands this…

Computer Vision and Pattern Recognition · Computer Science 2013-06-07 Eckhard Hitzer

In this paper I present a kind of proof for classical Euclidean geometric problems which relies on both synthetic and analytic geometry. Using the elementary tools of polynomial algebra and multivariate calculus we manage to reduce the…

Algebraic Geometry · Mathematics 2020-05-05 Davide Antonio Nello Maran

Generalized symmetries (also known as categorical symmetries) is a newly developing technique for studying quantum field theories. It has given us new insights into the structure of QFT and many new powerful tools that can be applied to the…

High Energy Physics - Phenomenology · Physics 2023-06-06 T. Daniel Brennan , Sungwoo Hong

A discrete conformality for polyhedral metrics on surfaces is introduced in this paper which generalizes earlier work on the subject. It is shown that each polyhedral metric on a surface is discrete conformal to a constant curvature…

Geometric Topology · Mathematics 2013-09-18 Xianfeng Gu , Feng Luo , Jian Sun , Tianqi Wu

Differential forms is a highly geometric formalism for physics used from field theories to General Relativity (GR) which has been a great upgrade over vector calculus with the advantages of being coordinate-free and carrying a high degree…

General Relativity and Quantum Cosmology · Physics 2024-07-26 Pablo Bañón Pérez , Maarten DeKieviet

We discuss umbral calculus as a method of systematically discretizing linear differential equations while preserving their point symmetries as well as generalized symmetries. The method is then applied to the Schr\"{o}dinger equation in…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Decio Levi , Piergiulio Tempesta , Pavel Winternitz

Neural representations of 3D data have been widely adopted across various applications, particularly in recent work leveraging coordinate-based networks to model scalar or vector fields. However, these approaches face inherent challenges,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Biao Zhang , Jing Ren , Peter Wonka
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