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We study the local approximation properties in hierarchical spline spaces through multiscale quasi-interpolation operators. This construction suggests the analysis of a subspace of the classical hierarchical spline space (Vuong et al.,…

Numerical Analysis · Mathematics 2015-07-24 Annalisa Buffa , Eduardo M. Garau

There are many significant applied contexts that require the solution of discontinuous optimization problems in finite dimensions. Yet these problems are very difficult, both computationally and analytically. With the functions being…

Optimization and Control · Mathematics 2023-05-25 Ying Cui , Junyi Liu , Jong-Shi Pang

This paper explores an efficient Lagrangian approach for evolving point cloud data on smooth manifolds. In this preliminary study, we focus on analyzing plane curves, and our ultimate goal is to provide an alternative to the conventional…

Numerical Analysis · Mathematics 2025-10-03 Muhammad Ammad , Leevan Ling

The solution approximation for partial differential equations (PDEs) can be substantially improved using smooth basis functions. The recently introduced mollified basis functions are constructed through mollification, or convolution, of…

Numerical Analysis · Mathematics 2024-07-01 Dewangga Alfarisy , Lavi Zuhal , Michael Ortiz , Fehmi Cirak , Eky Febrianto

This paper provides a survey of spherical designs and their applications, with a particular emphasis on the perspective of ``numerical analysis''. A set \(X_N\) of \(N\) points on the unit sphere \(\mathbb{S}^d\) is called a…

Numerical Analysis · Mathematics 2026-01-21 Congpei An , Xiaosheng Zhuang

Understanding the capacity of quantum circuits through the lens of approximation theory is essential for evaluating the complexity of quantum circuits required to solve various problems in scientific computation. We design quantum circuits…

Quantum Physics · Physics 2025-09-03 Junaid Aftab , Haizhao Yang

With the renewed and growing interest in geometric continuity in mind, this article gives a general definition of geometrically continuous polygonal surfaces and geometrically continuous spline functions on them. Polynomial splines defined…

Differential Geometry · Mathematics 2015-10-27 Raimundas Vidunas

The piecewise-concave function may be used to approximate a wide range of other functions to arbitrary precision over a bounded set. In this short paper, this property is proven for three function classes: (a) the multivariate twice…

Optimization and Control · Mathematics 2014-04-18 Gene A. Bunin

In a previous paper it was shown that a machine learning regression problem can be solved within the framework of random function theory, with the optimal kernel analytically derived from symmetry and indifference principles and coinciding…

Machine Learning · Computer Science 2025-12-19 Yuriy N. Bakhvalov

This paper presents a learning-based method to solve the traditional parameterization and knot placement problems in B-spline approximation. Different from conventional heuristic methods or recent AI-based methods, the proposed method does…

Computational Engineering, Finance, and Science · Computer Science 2024-06-17 Qiang Zou , Lizhen Zhu

In this paper, we describe a general class of $C^1$ smooth rational splines that enables, in particular, exact descriptions of ellipses and ellipsoids - some of the most important primitives for CAD and CAE. The univariate rational splines…

Numerical Analysis · Mathematics 2020-12-08 Hendrik Speleers , Deepesh Toshniwal

In this work, we present some new integration formulas for any order of accuracy as an application of the B-spline relations obtained in [1]. The resulting rules are defined as a perturbation of the trapezoidal integration method. We prove…

Numerical Analysis · Mathematics 2024-05-21 Dionisio F. Yáñez

We consider overlap splines that are defined by connecting the patches of piecewise functions via common values at given finite sets of nodes, without using any partitions of the computational domain. It is shown that some classical finite…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

In this paper, we present a simple yet effective padding scheme that can be used as a drop-in module for existing convolutional neural networks. We call it partial convolution based padding, with the intuition that the padded region can be…

Computer Vision and Pattern Recognition · Computer Science 2018-11-29 Guilin Liu , Kevin J. Shih , Ting-Chun Wang , Fitsum A. Reda , Karan Sapra , Zhiding Yu , Andrew Tao , Bryan Catanzaro

We present a principled study on establishing a recursive Bayesian estimation scheme using B-splines in Euclidean spaces. The use of recurrent control points as the state vector is first conceptualized in a recursive setting. This enables…

Systems and Control · Electrical Eng. & Systems 2025-06-12 Kailai Li

In the present paper we introduce the class of slice-polynomial functions: slice regular functions {defined over the quaternions, outside the real axis,} whose restriction to any complex half-plane is a polynomial. These functions naturally…

Complex Variables · Mathematics 2019-01-03 Amedeo Altavilla , Giulia Sarfatti

We uncover an unexpected connection between the physics of loop integrals and the mathematics of spline functions. One loop integrands are Laplace transforms of splines. This clarifies the geometry of the associated loop integrals, since a…

High Energy Physics - Theory · Physics 2015-06-11 Miguel F. Paulos

In implementations of the functional data methods, the effect of the initial choice of an orthonormal basis has not gained much attention in the past. Typically, several standard bases such as Fourier, wavelets, splines, etc. are considered…

Machine Learning · Statistics 2021-03-15 Rani Basna , Hiba Nassar , Krzysztof Podgórski

In this paper, we investigate $C^2$ super-smoothness of the full $C^1$ cubic spline space on a Powell-Sabin refined triangulation, for which a B-spline basis can be constructed. Blossoming is used to identify the $C^2$ smoothness conditions…

Numerical Analysis · Mathematics 2024-11-11 Jan Grošelj , Hendrik Speleers

Additive utility function models are widely used in multiple criteria decision analysis. In such models, a numerical value is associated to each alternative involved in the decision problem. It is computed by aggregating the scores of the…

Optimization and Control · Mathematics 2017-10-05 Olivier Sobrie , Nicolas Gillis , Vincent Mousseau , Marc Pirlot