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We present the Fast Chebyshev Transform (FCT), a fast, randomized algorithm to compute a Chebyshev approximation of functions in high-dimensions from the knowledge of the location of its nonzero Chebyshev coefficients. Rather than sampling…

Numerical Analysis · Mathematics 2023-10-03 Dalton Jones , Pierre-David Letourneau , Matthew J. Morse , M. Harper Langston

We consider the problem of computing the topology and describing the geometry of a parametric curve in $\mathbb{R}^n$. We present an algorithm, PTOPO, that constructs an abstract graph that is isotopic to the curve in the embedding space.…

Symbolic Computation · Computer Science 2022-02-18 Christina Katsamaki , Fabrice Rouillier , Elias Tsigaridas

We consider the problem of approximating a two-dimensional shape contour (or curve segment) using discrete assembly systems, which allow to build geometric structures based on limited sets of node and edge types subject to edge length and…

Computational Geometry · Computer Science 2021-02-03 Andreas M. Tillmann , Leif Kobbelt

The implicit theory that a simulation represents is precisely not in the individual choices but rather in the 'envelope' of possible trajectories - what is important is the shape of the whole envelope. Typically a huge amount of computation…

Programming Languages · Computer Science 2007-05-23 Oswaldo Teran , Bruce Edmonds , Steve Wallis

There is presented an approach to find an approximation polynomial of a function with two variables based on the two dimensional discrete Fourier transform. The approximation polynomial is expressed through Chebyshev polynomials. There is…

Numerical Analysis · Mathematics 2015-04-21 Ernest Scheiber

Chebyshev coefficients of a coordinate representation can be used to form the corresponding velocity representation. One way is to directly apply them to the derivatives of Chebyshev polynomials, another is to compute from them the…

Instrumentation and Methods for Astrophysics · Physics 2018-07-03 Yanning Fu

Orthogonal polynomials have very useful properties in the solution of mathematical problems, so recent years have seen a great deal in the field of approximation theory using orthogonal polynomials. In this paper, we characterize the…

Classical Analysis and ODEs · Mathematics 2015-10-30 Mohammad A. AlQudah

In this work the implicit function theorem is used for searching local symbolic resolution of differential equations. General results of existence for first order equations are proven and some examples, one relative to cavitation in a…

Numerical Analysis · Mathematics 2025-10-20 Gianluca Argentini

Deep networks often exhibit a preference for "simple" solutions, and such a simplicity bias is widely believed to play a key role in generalization. Yet a broadly applicable, quantitative measure of simplicity remains elusive. We introduce…

Artificial Intelligence · Computer Science 2026-05-29 Tianren Zhang , Xiangxin Li , Minghao Xiao , Guanyu Chen , Feng Chen

Recent years have witnessed the introduction and development of extremely fast rational function algorithms. Many ideas in this realm arose from polynomial-based linear-algebraic algorithms. However, polynomial approximation is occasionally…

Numerical Analysis · Mathematics 2025-10-03 James Chok , Geoffrey M. Vasil

We enhance the approximation capabilities of algebraic polynomials by composing them with homeomorphisms. This composition yields families of functions that remain dense in the space of continuous functions, while enabling more accurate…

Numerical Analysis · Mathematics 2025-12-17 Álvaro Fernández Corral , Yahya Saleh

In variational inference, the benefits of Bayesian models rely on accurately capturing the true posterior distribution. We propose using neural samplers that specify implicit distributions, which are well-suited for approximating complex…

Machine Learning · Computer Science 2023-11-10 Anshuk Uppal , Kristoffer Stensbo-Smidt , Wouter Boomsma , Jes Frellsen

Rational best approximations (in a Chebyshev sense) to real functions are characterized by an equioscillating approximation error. Similar results do not hold true for rational best approximations to complex functions in general. In the…

Numerical Analysis · Mathematics 2023-12-22 Tobias Jawecki , Pranav Singh

Recently, the butterfly approximation scheme and hierarchical approximations have been proposed for the efficient computation of integral transforms with oscillatory and with asymptotically smooth kernels. Combining both approaches, we…

Numerical Analysis · Mathematics 2016-06-13 Stefan Kunis , Ines Melzer

Diffusive representations of fractional derivatives have proven to be useful tools in the construction of fast and memory efficient numerical methods for solving fractional differential equations. A common challenge in many of the known…

Numerical Analysis · Mathematics 2022-04-11 Kai Diethelm

Orthogonalization is one of few mathematical methods conforming to mathematical standards for approximation. Finding a consistent PC matrix of a given an inconsistent PC matrix is the main goal of a pairwise comparisons method. We introduce…

Numerical Analysis · Mathematics 2024-04-25 Julio Benitez , Waldemar W. Koczkodaj , Adam Kowalczyk

For a function that is analytic on and around an interval, Chebyshev polynomial interpolation provides spectral convergence. However, if the function has a singularity close to the interval, the rate of convergence is near one. In these…

Numerical Analysis · Mathematics 2017-08-10 Kevin W. Aiton , Tobin A. Driscoll

Because of the high approximation power and simplicity of computation of smooth radial basis functions (RBFs), in recent decades they have received much attention for function approximation. These RBFs contain a shape parameter that…

Numerical Analysis · Mathematics 2023-06-23 Fatemeh Pooladi , Hossein Hosseinzadeh

Results of number of geometric operations (often used in technical practise, as e.g. the operation of blending) are in many cases surfaces described implicitly. Then it is a challenging task to recognize the type of the obtained surface,…

Symbolic Computation · Computer Science 2014-07-11 Jan Vršek , Miroslav Lávička

Any solid object can be decomposed into a collection of convex polytopes (in short, convexes). When a small number of convexes are used, such a decomposition can be thought of as a piece-wise approximation of the geometry. This…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Boyang Deng , Kyle Genova , Soroosh Yazdani , Sofien Bouaziz , Geoffrey Hinton , Andrea Tagliasacchi
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