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In this paper approximations of three classes of fractional derivatives (FD) using modified Gauss integration (MGI) and Gauss-Laguerre integration (GLI) are considered. The main solutions of these fractional derivatives depend on inverse of…

Numerical Analysis · Mathematics 2015-03-14 H. Fallahgoul , S. M. Hashemiparast

In this paper, we investigate the geometric invariant properties of a normal curve on a smooth immersed surface under conformal transformation. We obtain an invariant-sufficient condition for the conformal image of a normal curve. We also…

General Mathematics · Mathematics 2019-08-12 Mohamd Saleem Lone

We derive a Dickman approximation for the small jumps of a large class of multivariate L\'evy processes. We then apply this approximation to develop a simulation method for the class of general multivariate gamma distributions (GMGD). A…

Probability · Mathematics 2025-09-19 Michael Grabchak , Xingnan Zhang

This is the first of two papers where we address and partially confirm a conjecture of Deser and Schwimmer, originally postulated in high energy physics. The objects of study are scalar Riemannian quantities constructed out of the curvature…

Differential Geometry · Mathematics 2016-09-07 Spyros Alexakis

We study differential geometric properties of cuspidal edges with boundary. There are several differential geometric invariants which are related with the behavior of the boundary in addition to usual differential geometric invariants of…

Differential Geometry · Mathematics 2016-11-01 Luciana F. Martins , Kentaro Saji

Due to the principle of minimal information gain, the measurement of points in an affine space $V$ determines a Legendrian submanifold of $V \times V^* \times \mathbb R$. Such Legendrian submanifolds are equipped with additional geometric…

Mathematical Physics · Physics 2020-10-28 Eivind Schneider

We develop a new statistical model for photographic images, in which the local responses of a bank of linear filters are described as jointly Gaussian, with zero mean and a covariance that varies slowly over spatial position. We optimize…

Computer Vision and Pattern Recognition · Computer Science 2015-03-25 Olivier J. Hénaff , Johannes Ballé , Neil C. Rabinowitz , Eero P. Simoncelli

The Gaussian graphical model (GGM) incorporates an undirected graph to represent the conditional dependence between variables, with the precision matrix encoding partial correlation between pair of variables given the others. To achieve…

Methodology · Statistics 2023-07-03 Yueqi Qian , Xianghong Hu , Can Yang

We consider variational problems that model the bending behavior of curves that are constrained to belong to given hypersurfaces. Finite element discretizations of corresponding functionals are justified rigorously via Gamma-convergence.…

Numerical Analysis · Mathematics 2020-04-24 Sören Bartels

This paper studies how to capture dependency graph structures from real data which may not be Gaussian. Starting from marginal loss functions not necessarily derived from probability distributions, we utilize an additive…

Machine Learning · Statistics 2019-12-03 Yiyuan She , Shao Tang , Qiaoya Zhang

We present identities for permutations with fixed points. The formulas are based on successive derivations or integrations of the determinant of a particular matrix.

Combinatorics · Mathematics 2025-11-10 Jean-Christophe Pain

In this paper, we design two fundamental differential operators for the derivation of rotation differential invariants of images. Each differential invariant obtained by using the new method can be expressed as a homogeneous polynomial of…

Computer Vision and Pattern Recognition · Computer Science 2021-03-16 Hanlin Mo , Hua Li

We apply a novel method for the equivalence group and its infinitesimal generators to the investigation of invariants of linear ordinary differential equations. First, a comparative study of this method is illustrated by an example. Next,…

Analysis of PDEs · Mathematics 2008-06-27 J. C. Ndogmo

We propose a novel Bayesian nonparametric method to learn translation-invariant relationships on non-Euclidean domains. The resulting graph convolutional Gaussian processes can be applied to problems in machine learning for which the input…

Machine Learning · Computer Science 2019-05-15 Ian Walker , Ben Glocker

In this paper we show how the well-know local symmetries of Lagrangeans systems, and in particular the diffeomorphism invariance, emerge in the Hamiltonian formulation. We show that only the constraints which are linear in the momenta…

High Energy Physics - Theory · Physics 2010-11-01 V. Mukhanov , A. Wipf

For general non-Gaussian distributions, the covariance and precision matrices do not encode the independence structure of the variables, as they do for the multivariate Gaussian. This paper builds on previous work to show that for a class…

Machine Learning · Computer Science 2025-08-18 Ujas Shah , Manuel Lladser , Rebecca Morrison

Pan-sharpening algorithms utilize a panchromatic image and a multispectral image to generate a high spatial and high spectral image. However, the optimizations of the algorithms are designed with different standards. We employ a simple…

Machine Learning · Computer Science 2025-07-17 Shiqi Liu , Yihua Tan , Yutong Bai , Alan Yuille

The slightly subtle notion of covariant Lie derivatives of \textit{bundle-valued} differential forms is crucial in many applications in physics, notably in the computation of conserved currents in gauge theories, and yet the literature on…

Mathematical Physics · Physics 2025-07-02 Grigorios Giotopoulos

The aim of the paper is to understand the local forms of conformal vector fields in the neighborhood of a singularity. We begin a general study in this direction, for any pseudo-Riemannian type, and give a complete answer in the Riemannian…

Differential Geometry · Mathematics 2010-08-17 Charles Frances

We study a non local approximation of the Gaussian perimeter, proving the Gamma convergence to the local one. Surprisingly, in contrast with the local setting, the halfspace turns out to be a volume constrained stationary point if and only…

Analysis of PDEs · Mathematics 2020-11-17 Antonio De Rosa , Domenico Angelo La Manna
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