English
Related papers

Related papers: Differentiation in Bundles with a Hyperspace Base

200 papers

An action of a Lie algebra $\frak g$ on a manifold $M$ is just a Lie algebra homomorphism $\zeta:\frak g\to \frak X(M)$. We define orbits for such an action. In general the space of orbits $M/\frak g$ is not a manifold and even has a bad…

Differential Geometry · Mathematics 2016-09-06 Dimitri Alekseevsky , Peter W. Michor

In this paper we introduce hyperations and cohyperations, which are forms of transfinite iteration of ordinal functions. Hyperations are iterations of normal functions. Unlike iteration by pointwise convergence, hyperation preserves…

Logic · Mathematics 2012-05-10 David Fernández-Duque , Joost J. Joosten

We present a novel approach for high-order accurate numerical differentiation on unstructured meshes of quadrilateral elements. To differentiate a given function, an auxiliary function with greater smoothness properties is defined which…

Numerical Analysis · Mathematics 2022-05-11 Yulong Pan , Per-Olof Persson

Radial basis functions (RBFs) are prominent examples for reproducing kernels with associated reproducing kernel Hilbert spaces (RKHSs). The convergence theory for the kernel-based interpolation in that space is well understood and optimal…

Classical Analysis and ODEs · Mathematics 2023-09-15 Thomas Hangelbroek , Christian Rieger

The ability of deep networks to learn superior representations hinges on leveraging the proper inductive biases, considering the inherent properties of datasets. In tabular domains, it is critical to effectively handle heterogeneous…

Machine Learning · Computer Science 2024-05-15 Kyungeun Lee , Ye Seul Sim , Hye-Seung Cho , Moonjung Eo , Suhee Yoon , Sanghyu Yoon , Woohyung Lim

We apply the topology of convergence on compact sets to define unpredictable functions [5, 6]. The topology is metrizable and easy for applications with integral operators. To demonstrate the effectiveness of the approach, the existence and…

Chaotic Dynamics · Physics 2016-11-17 Marat Akhmet , Mehmet Onur Fen

We present a method for calculating the results of operation of differential operators operating on components of vector in generalized coordinates not restricted to orthogonal one. For this we use the relationships between covariant,…

General Physics · Physics 2025-08-27 Priyabrata Mitra , Dhrubaditya Mitra

Ultrafunctions are a particular class of functions defined on a Non Archimedean field E. They have been introduced and studied in some previous works. In this paper we develop the notion of fine ultrafunctions which improves the older…

Analysis of PDEs · Mathematics 2022-03-14 Vieri Benci

We give an algorithm to write down all conformally invariant differential operators acting between scalar functions on Minkowski space. All operators of order k are nonlinear and are functions on a finite family of functionally independent…

Mathematical Physics · Physics 2007-05-23 Petko Nikolov , Tihomir Valchev

We define a class of discrete operators acting on infinite, finite or periodic sequences mimicking the standard properties of pseudo-differential operators. In particular we can define the notion of order and regularity, and we recover the…

Analysis of PDEs · Mathematics 2021-10-01 Erwan Faou , Benoît Grébert

We consider the problem of constructing an action functional for physical systems whose classical equations of motion cannot be directly identified with Euler-Lagrange equations for an action principle. Two ways of action principle…

Mathematical Physics · Physics 2009-07-06 D. M. Gitman , V. G. Kupriyanov

We investigate gauge anomalies in the context of orbifold conformal field theories. Such anomalies manifest as failures of modular invariance in the constituents of the orbifold partition function. We review how this irregularity is…

High Energy Physics - Theory · Physics 2021-10-13 Daniel Robbins , Eric Sharpe , Thomas Vandermeulen

Despite their widespread success, the application of deep neural networks to functional data remains scarce today. The infinite dimensionality of functional data means standard learning algorithms can be applied only after appropriate…

Machine Learning · Statistics 2021-06-22 Junwen Yao , Jonas Mueller , Jane-Ling Wang

We provide two new formulations of the separativity problem. First, it is known that separativity (and strong separativity) in von Neumann regular (and exchange) rings is tightly connected to unit-regularity of certain kinds of elements. By…

Rings and Algebras · Mathematics 2024-03-19 Pere Ara , Ken Goodearl , Pace P. Nielsen , Enrique Pardo , Francesc Perera

Abstract convexity generalises classical convexity by considering the suprema of functions taken from an arbitrarily defined set of functions. These are called the abstract linear (abstract affine) functions. The purpose of this paper is to…

Optimization and Control · Mathematics 2025-01-30 Reinier Diàz Millàn , Nadezda Sukhorukova , Julien Ugon

This paper develops the theory of a sheaf of normal differential operators to a submanifold Y of a complex manifold X as a generalization of the normal bundle. We show that the global sections of this sheaf play an analogous role for formal…

Algebraic Geometry · Mathematics 2007-05-23 Paul Burchard , Herb Clemens

In this research, the Bernoulli polynomials are introduced. The properties of these polynomials are employed to construct the operational matrices of integration together with the derivative and product. These properties are then utilized…

Numerical Analysis · Computer Science 2014-08-12 J. A. Rad , S. Kazem , M. Shaban , K. Parand

The differential calculus on `non-standard' $h$-Minkowski spaces is given. In particular it is shown that, for them, it is possible to introduce coordinates and derivatives which are simultaneously hermitian.

q-alg · Mathematics 2011-07-13 J. A. de Azcárraga , F. Rodenas

The divergence-like operator on an odd symplectic superspace which acts invariantly on a specially chosen odd vector field is considered. This operator is used to construct an odd invariant semidensity in a geometrically clear way. The…

dg-ga · Mathematics 2009-10-30 O. M. Khudaverdian

This paper addresses the problem of accurately estimating a function on one domain when only its discrete samples are available on another domain. To answer this challenge, we utilize a neural network, which we train to incorporate prior…

Machine Learning · Computer Science 2024-05-20 Guy Hay , Nir Sharon
‹ Prev 1 4 5 6 7 8 10 Next ›