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In this paper we investigate polynomial interpolation using orthogonal polynomials. We use weight functions associated with orthogonal polynomials to define a weighted form of Lagrange interpolation. We introduce an upper bound of error…

Numerical Analysis · Mathematics 2019-10-23 Maha Youssef , Gerd Baumann

Exploiting the deep generative model's remarkable ability of learning the data-manifold structure, some recent researches proposed a geometric data interpolation method based on the geodesic curves on the learned data-manifold. However,…

Machine Learning · Computer Science 2019-01-25 Jiseob Kim , Byoung-Tak Zhang

Topology optimization is one of the engineering tools for finding efficient design. For the material interpolation scheme, it is usual to employ the SIMP (Solid Isotropic Material with Penalization) or the homogenization based interpolation…

Computational Engineering, Finance, and Science · Computer Science 2022-12-07 Bing Yi , Gil Ho Yoon , Ran Zheng , Long Liu , Daping Li , Xiang Peng

We consider the problem of interpolating a function given on scattered points using Hermite-Birkhoff formulas on the sphere and other manifolds. We express each proposed interpolant as a linear combination of basis functions, the…

Numerical Analysis · Mathematics 2016-11-23 Giampietro Allasia , Roberto Cavoretto , Alessandra De Rossi

We propose Framer for interactive frame interpolation, which targets producing smoothly transitioning frames between two images as per user creativity. Concretely, besides taking the start and end frames as inputs, our approach supports…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Wen Wang , Qiuyu Wang , Kecheng Zheng , Hao Ouyang , Zhekai Chen , Biao Gong , Hao Chen , Yujun Shen , Chunhua Shen

We examine the necessity of interpolation in overparameterized models, that is, when achieving optimal predictive risk in machine learning problems requires (nearly) interpolating the training data. In particular, we consider simple…

Machine Learning · Statistics 2022-06-17 Chen Cheng , John Duchi , Rohith Kuditipudi

The recovery of the intrinsic geometric structures of data collections is an important problem in data analysis. Supervised extensions of several manifold learning approaches have been proposed in the recent years. Meanwhile, existing…

Computer Vision and Pattern Recognition · Computer Science 2018-05-29 Cem Ornek , Elif Vural

For a family of weight functions that include the general Jacobi weight functions as special cases, exact condition for the convergence of the Fourier orthogonal series in the weighted $L^p$ space is given. The result is then used to…

Numerical Analysis · Mathematics 2025-10-20 P. Vertesi , Yuan Xu

This paper presents a super-resolution method based on gradient-based adaptive interpolation. In this method, in addition to considering the distance between the interpolated pixel and the neighboring valid pixel, the interpolation…

Multimedia · Computer Science 2009-03-25 Jinyu Chu , Ju Liu , Jianping Qiao , Xiaoling Wang , Yujun Li

Training classifiers under fairness constraints such as group fairness, regularizes the disparities of predictions between the groups. Nevertheless, even though the constraints are satisfied during training, they might not generalize at…

Machine Learning · Computer Science 2021-03-12 Ching-Yao Chuang , Youssef Mroueh

Supervised manifold learning methods for data classification map data samples residing in a high-dimensional ambient space to a lower-dimensional domain in a structure-preserving way, while enhancing the separation between different classes…

Computer Vision and Pattern Recognition · Computer Science 2016-04-20 Elif Vural , Christine Guillemot

Multivariate functional data has received considerable attention but testing for equality of mean surfaces and its profile has limited progress. The existing literature has tested equality of either mean curves of univariate functional…

Methodology · Statistics 2019-03-07 Jin Yang , Tao Zhang , Chunling Liu , Kam Chuen Yuen , Aiyi Liu

Video frame interpolation, the synthesis of novel views in time, is an increasingly popular research direction with many new papers further advancing the state of the art. But as each new method comes with a host of variables that affect…

Computer Vision and Pattern Recognition · Computer Science 2020-11-04 Simon Niklaus , Long Mai , Oliver Wang

Recovering the missing regions of an image is a task that is called image inpainting. Depending on the shape of missing areas, different methods are presented in the literature. One of the challenges of this problem is extracting features…

Computer Vision and Pattern Recognition · Computer Science 2020-01-13 Ghazale Ghorbanzade , Zahra Nabizadeh , Nader Karimi , Shadrokh Samavi

Video frame interpolation (VFI) works generally predict intermediate frame(s) by first estimating the motion between inputs and then warping the inputs to the target time with the estimated motion. This approach, however, is not optimal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Dawit Mureja Argaw , In So Kweon

This paper addresses the problem of approximating a function of bounded variation from its scattered data. Radial basis function(RBF) interpolation methods are known to approximate only functions in their native spaces, and to date, there…

Numerical Analysis · Mathematics 2025-12-23 Rajesh Dachiraju

We introduce intrinsic interpolatory bases for data structured on graphs and derive properties of those bases. Polyharmonic Lagrange functions are shown to satisfy exponential decay away from their centers. The decay depends on the density…

Numerical Analysis · Mathematics 2020-04-21 John Paul Ward , Francis J. Narcowich , Joseph D. Ward

Background and aim: Most of the Mixed Reality models used in the surgical telepresence are suffering from discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim…

Here the polynomial interpolation approach is used to introduce the main results on multivariate normal algebraic systems. Next we bring a construction which shows that any standard algebraic system, with finite set of solutions, can be…

Numerical Analysis · Mathematics 2025-10-20 H. Hakopian

An interpolation error is an integral of the squared error of a regression model over a domain of interest. We consider the interpolation error for the case of misspecified Gaussian process regression: used covariance function differs from…

Statistics Theory · Mathematics 2018-03-28 A. Zaytsev , E. Romanenkova , D. Ermilov