English
Related papers

Related papers: Random points on an algebraic manifold

200 papers

We are interested in comparing probability distributions defined on Riemannian manifold. The traditional approach to study a distribution relies on locating its mean point and finding the dispersion about that point. On a general manifold…

Statistics Theory · Mathematics 2008-07-22 Nikolay H. Balov

In this paper we present the set of intervals as a normed vector space. We define also a four-dimensional associative algebra whose product gives the product of intervals in any cases. This approach allows to give a notion of divisibility…

Numerical Analysis · Computer Science 2009-10-22 Nicolas Goze , Elisabeth Remm

We produce algorithms to detect whether a complex affine variety computed and presented numerically by the machinery of numerical algebraic geometry corresponds to an associated component of a polynomial ideal.

Algebraic Geometry · Mathematics 2016-01-15 Robert Krone , Anton Leykin

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such…

Numerical Analysis · Mathematics 2016-02-17 Philipp Hennig , Michael A Osborne , Mark Girolami

We describe a numerical framework that uses random sampling to efficiently capture low-rank local solution spaces of multiscale PDE problems arising in domain decomposition. In contrast to existing techniques, our method does not rely on…

Numerical Analysis · Mathematics 2020-02-06 Ke Chen , Qin Li , Jianfeng Lu , Stephen J. Wright

We establish sharp estimates that adapt the polynomial method to arbitrary varieties. These include a partitioning theorem, estimates on polynomials vanishing on fixed sets and bounds for the number of connected components of real algebraic…

Algebraic Geometry · Mathematics 2020-06-15 Miguel N. Walsh

Modern sample points in many applications no longer comprise real vectors in a real vector space but sample points of much more complex structures, which may be represented as points in a space with a certain underlying geometric structure,…

Machine Learning · Statistics 2022-02-07 Zhigang Yao , Bingjie Li , Wee Chin Tan

We consider the problem of computing sample points in each connected component of a semi-algebraic set defined by the non-vanishing or the positivity of an n-variate polynomial of degree d, with rational coefficients of bit size bounded by…

Symbolic Computation · Computer Science 2026-05-27 Jérémy Berthomieu , Edern Gillot , Mohab Safey El Din

We introduce an algorithm for computing geodesics on sampled manifolds that relies on simulation of quantum dynamics on a graph embedding of the sampled data. Our approach exploits classic results in semiclassical analysis and the…

Quantum Physics · Physics 2022-01-13 Akshat Kumar , Mohan Sarovar

We prove the existence of infinitely many solutions to an elliptic problem by borrowing the techniques from algebraic topology. The solution(s) thus obtained will also be proved to be bounded.

Analysis of PDEs · Mathematics 2021-02-25 A. Panda , D. Choudhuri , A. Bahrouni

A multi-cube method is developed for solving systems of elliptic and hyperbolic partial differential equations numerically on manifolds with arbitrary spatial topologies. It is shown that any three-dimensional manifold can be represented as…

Computational Physics · Physics 2015-06-11 Lee Lindblom , Bela Szilagyi

This paper begins with a description of methods for estimating image probability density functions that reflects the observation that such data is usually constrained to lie in restricted regions of the high-dimensional image space-not…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Peter Tu , Zhaoyuan Yang , Richard Hartley , Zhiwei Xu , Jing Zhang , Yiwei Fu , Dylan Campbell , Jaskirat Singh , Tianyu Wang

One approach to parametric and adaptive model reduction is via the interpolation of orthogonal bases, subspaces or positive definite system matrices. In all these cases, the sampled inputs stem from matrix sets that feature a geometric…

Numerical Analysis · Mathematics 2022-12-16 Ralf Zimmermann

Random geometric graphs are random graph models defined on metric measure spaces. A random geometric graph is generated by first sampling points from a metric space and then connecting each pair of sampled points independently with a…

Probability · Mathematics 2025-11-10 Han Huang , Pakawut Jiradilok , Elchanan Mossel

Manifold learning is a popular and quickly-growing subfield of machine learning based on the assumption that one's observed data lie on a low-dimensional manifold embedded in a higher-dimensional space. This thesis presents a mathematical…

Machine Learning · Computer Science 2020-11-04 Luke Melas-Kyriazi

Many statistical models are algebraic in that they are defined in terms of polynomial constraints, or in terms of polynomial or rational parametrizations. The parameter spaces of such models are typically semi-algebraic subsets of the…

Statistics Theory · Mathematics 2010-03-04 Mathias Drton , Seth Sullivant

In Hamiltonian systems subjected to periodic perturbations the stable and unstable manifolds of the unstable periodic orbits provide the dynamical "skeleton" that drives the mixing process and bounds the chaotic regions of the phase space.…

Plasma Physics · Physics 2016-10-05 David Ciro Taborda , Todd Edwin Evans , Iberê Luiz Caldas

There is presented an algorithm for computing the topological degree for a large class of polynomial mappings. As an application there is given an effective algebraic formula for the intersection number of a polynomial immersion M --> R^2m,…

Algebraic Geometry · Mathematics 2008-07-14 Iwona Karolkiewicz , Aleksandra Nowel , Zbigniew Szafraniec

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

Polygons are compound geometric objects, but when trying to understand the expected behavior of a large collection of random polygons -- or even to formalize what a random polygon is -- it is convenient to interpret each polygon as a point…

History and Overview · Mathematics 2019-09-23 Clayton Shonkwiler