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We present a new approach to using neural networks to approximate the solutions of variational equations, based on the adaptive construction of a sequence of finite-dimensional subspaces whose basis functions are realizations of a sequence…

Machine Learning · Computer Science 2021-06-01 Mark Ainsworth , Justin Dong

Let $\epsilon>0$. In this article we will present a deterministic algorithm which does the following. The input is a hyperelliptic curve $C$ of genus $g$ over a finite field $k$ of cardinality $q$ given by $y^2+h(x)y=f(x)$ such that the…

Number Theory · Mathematics 2014-02-27 Michiel Kosters

We show how random vectors and random projection can be implemented in the usual vector space model to construct a Euclidean semantic space from a French synonym dictionary. We evaluate theoretically the resulting noise and show the…

Computation and Language · Computer Science 2017-03-08 Jean-François Delpech , Sabine Ploux

Gaussian random number generators attract a widespread interest due to their applications in several fields. Important requirements include easy implementation, tail accuracy, and, finally, a flat spectrum. In this work, we study the…

Information Theory · Computer Science 2024-04-04 Francisco-Javier Soto , Ana I. Gómez , Domingo Gómez-Pérez

The ability to efficiently simulate random quantum circuits using a classical computer is increasingly important for developing Noisy Intermediate-Scale Quantum devices. Here we present a tensor network states based algorithm specifically…

Quantum Physics · Physics 2021-02-24 Chu Guo , Youwei Zhao , He-Liang Huang

Qualitative and quantitative aspects for variational inequalities governed by strongly pseudomonotone operators on Hilbert space are investigated in this paper. First, we establish a global error bound for the solution set of the given…

Optimization and Control · Mathematics 2020-10-07 Pham Tien Kha , Pham Duy Khanh

Pseudorandom number generators are required for many computational tasks, such as stochastic modelling and simulation. This paper investigates the serial CPU and parallel GPU implementation of a Linear Congruential Generator based on the…

Mathematical Software · Computer Science 2012-06-25 Gleb Beliakov , Michael Johnstone , Doug Creighton , Tim Wilkin

Random fields on the sphere play a fundamental role in the natural sciences. This paper presents a simulation algorithm parenthetical to the spectral turning bands method used in Euclidean spaces, for simulating scalar- or vector-valued…

Statistics Theory · Mathematics 2020-03-31 Alfredo Alegría , Xavier Emery , Christian Lantuéjoul

Our aim is to construct high order approximation schemes for general semigroups of linear operators $P_{t},t\geq 0$. In order to do it, we fix a time horizon $T $ and the discretization steps $h_{l}=\frac{T}{n^{l}},l\in \mathbb{N}$ and we…

Probability · Mathematics 2019-05-22 Aurélien Alfonsi , Vlad Bally

We introduce an algorithm for the uniform generation of infinite runs in concurrent systems under a partial order probabilistic semantics. We work with trace monoids as concurrency models. The algorithm outputs on-the-fly approximations of…

Combinatorics · Mathematics 2017-12-07 Samy Abbes , Vincent Jugé

We build a new class of generative algorithms capable of efficiently learning an arbitrary target distribution from possibly scarce, high-dimensional data and subsequently generate new samples. These generative algorithms are particle-based…

Machine Learning · Statistics 2024-08-29 Hyemin Gu , Panagiota Birmpa , Yannis Pantazis , Luc Rey-Bellet , Markos A. Katsoulakis

Space-filling curves like the Hilbert-curve, Peano-curve and Z-order map natural or real numbers from a two or higher dimensional space to a one dimensional space preserving locality. They have numerous applications like search structures,…

Machine Learning · Computer Science 2020-08-05 Christian Böhm

We represent vector bundles over a regular algebraic curve as pairs of lattices over the maximal orders of its function field and we give polynomial time algorithms for several tasks: computing determinants of vector bundles, kernels and…

Algebraic Geometry · Mathematics 2024-08-05 Mickaël Montessinos

Given the prevalence of superconducting platforms for uses in quantum computing and quantum sensing, the simulation of quantum superconducting circuits has become increasingly important for identifying system characteristics and modeling…

Quantum Physics · Physics 2026-03-09 Brittany Richman , C. J. Lobb , Jacob M. Taylor

We present a certified algorithm based on subdivision for computing an isotopic approximation to any number of curves in the plane. Our algorithm is based on the certified curve approximation algorithm of Plantinga and Vegter. The main…

Computational Geometry · Computer Science 2024-07-26 Michael Burr , Michael Byrd

We present a certified algorithm based on subdivision for computing an isotopic approximation to any number of curves in the plane. Our algorithm is based on the certified curve approximation algorithm of Plantinga and Vegter. The main…

Computational Geometry · Computer Science 2024-07-29 Michael Burr , Michael Byrd

We address here the problem of generating random graphs uniformly from the set of simple connected graphs having a prescribed degree sequence. Our goal is to provide an algorithm designed for practical use both because of its ability to…

Networking and Internet Architecture · Computer Science 2007-05-23 Fabien Viger , Matthieu Latapy

In this paper we provide an algorithm that generates a graph with given degree sequence uniformly at random. Provided that $\Delta^4=O(m)$, where $\Delta$ is the maximal degree and $m$ is the number of edges,the algorithm runs in expected…

Combinatorics · Mathematics 2021-01-25 Andrii Arman , Pu Gao , Nicholas Wormald

A low storage algorithm for constructing isogenies between ordinary elliptic curves was proposed by Galbraith, Hess and Smart (GHS). We give an improvement of this algorithm by modifying the pseudorandom walk so that lower-degree isogenies…

Number Theory · Mathematics 2011-06-01 Steven Galbraith , Anton Stolbunov

The Virtual Element Method (VEM) is a very effective framework to design numerical approximations with high global regularity to the solutions of elliptic partial differential equations. In this paper, we review the construction of such…

Numerical Analysis · Mathematics 2021-12-28 Paola Francesca Antonietti , Gianmarco Manzini , Simone Scacchi , Marco Verani
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