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This Note proposes a new methodology for function classification with Support Vector Machine (SVM). Rather than relying on projection on a truncated Hilbert basis as in our previous work, we use an implicit spline interpolation that allows…

Statistics Theory · Mathematics 2007-05-23 Nathalie Villa , Fabrice Rossi

In this work, we develop a class of high-order multiderivative time integration methods that is able to preserve certain functionals discretely. Important ingredients are the recently developed Hermite-Birkhoff-Predictor-Corrector methods…

Numerical Analysis · Mathematics 2023-09-12 Hendrik Ranocha , Jochen Schütz , Eleni Theodosiou

We construct and study a class of spectral graph wavelets by analogy with Hermitian wavelets on the real line. We provide a localization result that significantly improves upon those previously available, enabling application to highly…

Functional Analysis · Mathematics 2020-10-05 Zach Gelbaum , Mathew Titus , James Watson

We study multiscale scattered data interpolation schemes for globally supported radial basis functions with focus on the Mat\'ern class. The multiscale approximation is constructed through a sequence of residual corrections, where radial…

Numerical Analysis · Mathematics 2025-03-18 Sara Avesani , Rüdiger Kempf , Michael Multerer , Holger Wendland

Aims. We use Hermite splines to interpolate pressure and its derivatives simultaneously, thereby preserving mathematical relations between the derivatives. The method therefore guarantees that thermodynamic identities are obeyed even…

Solar and Stellar Astrophysics · Physics 2019-06-26 V. A. Baturin , W. Däppen , A. V. Oreshina , S. V. Ayukov , A. B. Gorshkov

Differential item functioning (DIF) detection is an important yet understudied problem in computerized adaptive testing (CAT). In this article, we proposed a two-level logistic model to improve DIF detection in CAT by explicitly accounting…

Applications · Statistics 2026-05-05 Dandan Chen Kaptur , Justin Kern , Chingwei David Shin , Jinming Zhang

The empirical wavelet transform is an adaptive multiresolution analysis tool based on the idea of building filters on a data-driven partition of the Fourier domain. However, existing 2D extensions are constrained by the shape of the…

Spectral Theory · Mathematics 2024-10-28 Basile Hurat , Zariluz Alvarado , Jerome Gilles

The band structure of the Lam\'e equation, viewed as a one-dimensional Schr\"odinger equation with a periodic potential, is studied. At integer values of the degree parameter l, the dispersion relation is reduced to the l=1 dispersion…

Mathematical Physics · Physics 2008-02-04 Robert S. Maier

We consider the applications of a numerical-analytical approach based on multiscale variational wavelet technique to the systems with collective type behaviour described by some forms of Vlasov-Poisson/Maxwell equations. We calculate the…

Accelerator Physics · Physics 2007-05-23 Antonina N. Fedorova , Michael G. Zeitlin

We relate Hilbert schemes of points and Fulton-MacPherson compactifications by an interpolating stability condition. We then derive wall-crossings formulas and some applications for the enumerative geometry of Hilbert schemes.

Algebraic Geometry · Mathematics 2025-01-15 Denis Nesterov

Matched wavelets interpolating equidistant data are designed. These wavelets form Riesz bases. Meyer wavelets that interpolate data on a particular uniform lattice are found.

Classical Analysis and ODEs · Mathematics 2020-06-19 Elena A. Lebedeva

To approximate solutions of a linear differential equation, we project, via trigonometric interpolation, its solution space onto a finite-dimensional space of trigonometric polynomials and construct a matrix representation of the…

Numerical Analysis · Mathematics 2011-08-30 Oksana Bihun , Austin Bren , Michael Dyrud , Kristin Heysse

The concepts of evaluation and interpolation are extended from univariate skew polynomials to multivariate skew polynomials, with coefficients over division rings. Iterated skew polynomial rings are in general not suitable for this purpose.…

Rings and Algebras · Mathematics 2018-11-02 Umberto Martínez-Peñas , Frank R. Kschischang

Wavelet Transforms are a widely used technique for decomposing a signal into coefficient vectors that correspond to distinct frequency/scale bands while retaining time localization. This property enables an adaptive analysis of signals at…

Applications · Statistics 2025-11-05 Jack Kissell , Vijini Lakmini , Brani Vidakovic

Bayesian change-point detection, together with latent variable models, allows to perform segmentation over high-dimensional time-series. We assume that change-points lie on a lower-dimensional manifold where we aim to infer subsets of…

Machine Learning · Statistics 2020-11-04 Lorena Romero-Medrano , Pablo Moreno-Muñoz , Antonio Artés-Rodríguez

In this paper, we study convergence and superconvergence theory of integer and fractional derivatives of the one-point and the two-point Hermite interpolations. When considering the integer-order derivative, exponential decay of the error…

Numerical Analysis · Mathematics 2018-03-22 Beichuan Deng , Jiwei Zhang , Zhimin Zhang

Discrete wavelets are applied to parametrization of the intra-chain two-point correlation functions of homopolymers in dilute solutions obtained from Monte Carlo simulation. Several orthogonal and biorthogonal basis sets have been…

Statistical Mechanics · Physics 2009-11-10 M. V. Fedorov , G. N. Chuev , Yu. A. Kuznetsov , E. G. Timoshenko

The wavelet transform, a family of orthonormal bases, is introduced as a technique for performing multiresolution analysis in statistical mechanics. The wavelet transform is a hierarchical technique designed to separate data sets into sets…

Chemical Physics · Physics 2009-11-07 Ahmed E. Ismail , Gregory C. Rutledge , George Stephanopoulos

In this paper we present a new multilevel quasi-interpolation algorithm for smooth periodic functions using scaled Gaussians as basis functions. Recent research in this area has focussed upon implementations using basis function with finite…

Numerical Analysis · Mathematics 2017-03-14 Simon Hubbert , Jeremy Levesley

Score-based models, trained with denoising score matching, are remarkably effective in generating high dimensional data. However, the high variance of their training objective hinders optimisation. We attempt to reduce it with a control…

Machine Learning · Computer Science 2024-08-23 Paul Jeha , Will Grathwohl , Michael Riis Andersen , Carl Henrik Ek , Jes Frellsen