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相关论文: A dynamic symbolic geometry environment based on t…

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We present a symbolic tool that provides robust algebraic methods to handle automatic deduction tasks for a dynamic geometry construction. The main prototype has been developed as two different worksheets for the open source computer…

数学软件 · 计算机科学 2012-02-23 Francisco Botana , Miguel A. Abánades

GeoGebra is an open source mathematics education software tool being used in thousands of schools worldwide. Since version 4.2 (December 2012) it supports symbolic computation of locus equations as a result of joint effort of mathematicians…

计算几何 · 计算机科学 2016-05-31 Francisco Botana , Zoltán Kovács

Polynomial system solving arises in many application areas to model non-linear geometric properties. In such settings, polynomial systems may come with degeneration which the end-user wants to exclude from the solution set. The…

符号计算 · 计算机科学 2023-06-12 Christian Eder , Pierre Lairez , Rafael Mohr , Mohab Safey El Din

We describe a prototype of a new experimental GeoGebra command and tool, Discover, that analyzes geometric figures for salient patterns, properties, and theorems. This tool is a basic implementation of automated discovery in elementary…

计算几何 · 计算机科学 2022-02-10 Zoltán Kovács , Jonathan H. Yu

A strong link between information geometry and algebraic statistics is made by investigating statistical manifolds which are algebraic varieties. In particular it it shown how first and second order efficient estimators can be constructed,…

统计理论 · 数学 2014-01-13 Kei Kobayashi , Henry P. Wynn

A model of a geometric algorithm is introduced and methodology of its operation is presented for the dynamic partitioning of data spaces.

数据结构与算法 · 计算机科学 2014-12-30 Christopher A. Tucker

The image of a polynomial map is a constructible set. While computing its closure is standard in computer algebra systems, a procedure for computing the constructible set itself is not. We provide a new algorithm, based on algebro-geometric…

代数几何 · 数学 2019-10-16 Corey Harris , Mateusz Michałek , Emre Can Sertöz

The representation of polynomials by arithmetic circuits evaluating them is an alternative data structure which allowed considerable progress in polynomial equation solving in the last fifteen years. We present a circuit based computation…

计算复杂性 · 计算机科学 2012-04-26 Joos Heintz , Bart Kuijpers , Andres Rojas Paredes

The field of numerical algebraic geometry consists of algorithms for numerically solving systems of polynomial equations. When the system is exact, such as having rational coefficients, the solution set is well-defined. However, for a…

数值分析 · 数学 2024-03-28 Emma R. Cobian , Jonathan D. Hauenstein , Charles W. Wampler

We propose a novel encoding scheme for algebraic codes such as codes on algebraic curves, multidimensional cyclic codes, and hyperbolic cascaded Reed-Solomon codes and present numerical examples. We employ the recurrence from the Gr\"obner…

信息论 · 计算机科学 2007-07-13 Hajime Matsui , Seiichi Mita

Exploiting internal spatial geometric constraints of sparse LiDARs is beneficial to depth completion, however, has been not explored well. This paper proposes an efficient method to learn geometry-aware embedding, which encodes the local…

计算机视觉与模式识别 · 计算机科学 2022-06-02 Wenchao Du , Hu Chen , Hongyu Yang , Yi Zhang

We describe a prototype of a new experimental GeoGebra command and tool Discover that analyzes geometric figures for salient patterns, properties, and theorems. This tool is a basic implementation of automated discovery in elementary planar…

人工智能 · 计算机科学 2020-07-27 Zoltán Kovács , Jonathan H. Yu

We describe a recursive algorithm that decomposes an algebraic set into locally closed equidimensional sets, i.e. sets which each have irreducible components of the same dimension. At the core of this algorithm, we combine ideas from the…

符号计算 · 计算机科学 2023-06-12 Christian Eder , Pierre Lairez , Rafael Mohr , Mohab Safey El Din

The problem of identifying geometric structure in data is a cornerstone of (unsupervised) learning. As a result, Geometric Representation Learning has been widely applied across scientific and engineering domains. In this work, we…

机器学习 · 计算机科学 2025-06-03 Imran Nasim , Melanie Weber

Classical unsupervised learning methods like clustering and linear dimensionality reduction parametrize large-scale geometry when it is discrete or linear, while more modern methods from manifold learning find low dimensional representation…

机器学习 · 计算机科学 2025-09-23 Luis Scoccola , Uzu Lim , Heather A. Harrington

The problem of mathematical modeling in geography is one of the most important strategies in order to establish the evolution and the prevision of geographical phenomena. Models must have a simplified structure, to reflect essential…

计算几何 · 计算机科学 2012-03-06 Ionica Soare , Carmen Antohe

The characterization of dynamical processes in living systems provides important clues for their mechanistic interpretation and link to biological functions. Thanks to recent advances in microscopy techniques, it is now possible to…

数据分析、统计与概率 · 物理学 2023-11-29 Jesús Pineda , Benjamin Midtvedt , Harshith Bachimanchi , Sergio Noé , Daniel Midtvedt , Giovanni Volpe , Carlo Manzo

Researchers working with mathematical models are often confronted by the related problems of parameter estimation, model validation, and model selection. These are all optimization problems, well-known to be challenging due to…

定量方法 · 定量生物学 2016-04-04 Elizabeth Gross , Brent Davis , Kenneth L. Ho , Daniel J. Bates , Heather A. Harrington

We present theory and practice for robust implementations of bivariate Jacobi set and Reeb space algorithms. Robustness is a fundamental topic in computational geometry that deals with the issues of numerical errors and degenerate cases in…

计算几何 · 计算机科学 2025-10-10 Petar Hristov , Ingrid Hotz , Talha Bin Masood

We present a novel certified and complete algorithm to compute arrangements of real planar algebraic curves. It provides a geometric-topological analysis of the decomposition of the plane induced by a finite number of algebraic curves in…

计算几何 · 计算机科学 2012-01-13 Eric Berberich , Pavel Emeliyanenko , Alexander Kobel , Michael Sagraloff
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