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A novel spherical convolution is defined through the sifting property of the Dirac delta on the sphere. The so-called sifting convolution is defined by the inner product of one function with a translated version of another, but with the…

Information Theory · Computer Science 2023-04-24 Patrick J. Roddy , Jason D. McEwen

We present a novel surface convolution operator acting on vector fields that is based on a simple observation: instead of combining neighboring features with respect to a single coordinate parameterization defined at a given point, we have…

Computer Vision and Pattern Recognition · Computer Science 2021-09-17 Thomas W. Mitchel , Vladimir G. Kim , Michael Kazhdan

Novel types of convolution operators for quaternion linear canonical transform (QLCT) are proposed. Type one and two are defined in the spatial and QLCT spectral domains, respectively. They are distinct in the quaternion space and are…

Classical Analysis and ODEs · Mathematics 2022-12-13 Xiaoxiao Hu , Dong Cheng , Kit Ian Kou

Spectral properties of many finite convolution integral operators have been understood by finding differential operators that commute with them. In this paper we compile a complete list of such commuting pairs, extending previous work to…

Classical Analysis and ODEs · Mathematics 2021-07-08 Yury Grabovsky , Narek Hovsepyan

The success of convolutional networks in learning problems involving planar signals such as images is due to their ability to exploit the translation symmetry of the data distribution through weight sharing. Many areas of science and…

Machine Learning · Computer Science 2019-04-23 Taco Cohen , Mario Geiger , Jonas Köhler , Max Welling

Spin-weighted spherical functions provide a useful tool for analyzing tensor-valued functions on the sphere. A tensor field can be decomposed into complex-valued functions by taking contractions with tangent vectors on the sphere and the…

General Relativity and Quantum Cosmology · Physics 2023-08-30 Michael Boyle

Convolutional Neural Networks (CNNs) have become the state-of-the-art in supervised learning vision tasks. Their convolutional filters are of paramount importance for they allow to learn patterns while disregarding their locations in input…

Machine Learning · Computer Science 2017-10-26 Jean-Charles Vialatte , Vincent Gripon , Grégoire Mercier

Motivated by the study of H\"ormander's sums-of-squares operators and their generalizations, we define the convolution algebra of transverse distributions associated to a singular foliation. We prove that this algebra is represented as…

Analysis of PDEs · Mathematics 2020-04-20 Iakovos Androulidakis , Omar Mohsen , Robert Yuncken

Quantum mechanics is often developed in the position representation, but this is not necessary, and one can perform calculations in a representation-independent fashion, even for wavefunctions. In this work, we illustrate how one can…

Quantum Physics · Physics 2021-07-28 Michael Rushka , Mark Esrick , Wesley N. Mathews , J. K. Freericks

Using simultaneously two operator identities, we consider the inversion of the convolution operators on a rectangular. The structure of the inverse operators and of some corresponding forms, which are important in signal processing, is…

Classical Analysis and ODEs · Mathematics 2017-01-31 Alexander Sakhnovich

We explicitly establish a unitary correspondence between spherical irreducible tensor operators and cartesian tensor operators of any rank. That unitary relation is implemented by means of a basis of integer-spin wave functions that…

Quantum Physics · Physics 2020-08-11 Antonio O. Bouzas

The wave equation for vectors and symmetric tensors in spherical coordinates is studied under the divergence-free constraint. We describe a numerical method, based on the spectral decomposition of vector/tensor components onto spherical…

General Relativity and Quantum Cosmology · Physics 2009-11-23 Jerome Novak , Jean-Louis Cornou , Nicolas Vasset

We develop theory and software for rotation equivariant operators on scalar and vector fields, with diverse applications in simulation, optimization and machine learning. Rotation equivariance (covariance) means all fields in the system…

Machine Learning · Computer Science 2022-08-08 Paul Shen , Michael Herbst , Venkat Viswanathan

We present a versatile formulation of the convolution operation that we term a "mapped convolution." The standard convolution operation implicitly samples the pixel grid and computes a weighted sum. Our mapped convolution decouples these…

Computer Vision and Pattern Recognition · Computer Science 2019-06-27 Marc Eder , True Price , Thanh Vu , Akash Bapat , Jan-Michael Frahm

In this article, we introduce and study the concept of $\textit{spherical-vectors}$, which can be perceived as a natural extension of the arguments of complex numbers in the context of quaternions. We initially establish foundational…

Rings and Algebras · Mathematics 2023-05-09 Lahcen Lamgouni

Analyzing scalar and vector fields on the sphere, such as temperature or wind speed and direction on Earth, is a difficult task. Models should respect both the rotational symmetries of the sphere and the inherent symmetries of the vector…

Machine Learning · Computer Science 2026-04-01 Francesco Ballerin , Nello Blaser , Erlend Grong

The free metaplectic transformation (FMT) is widely used in many fields such as filter design, pattern recognition, image processing and optics. In order to obtain a more concise and intuitive convolution form, this paper studies two kinds…

General Mathematics · Mathematics 2022-06-28 Hui Zhao , Bing-Zhao Li

The mathematical representations of data in the Spherical Harmonic (SH) domain has recently regained increasing interest in the machine learning community. This technical report gives an in-depth introduction to the theoretical foundation…

Machine Learning · Computer Science 2023-07-10 Janis Keuper

M\"obius transformations play an important role in both geometry and spherical image processing - they are the group of conformal automorphisms of 2D surfaces and the spherical equivalent of homographies. Here we present a novel,…

Computer Vision and Pattern Recognition · Computer Science 2022-05-16 Thomas W. Mitchel , Noam Aigerman , Vladimir G. Kim , Michael Kazhdan

In cosmological perturbation theory it is convenient to use the scalar, vector, tensor (SVT) basis as defined according to how these components transform under 3-dimensional rotations. In attempting to solve the fluctuation equations that…

General Relativity and Quantum Cosmology · Physics 2021-04-14 Matthew G. Phelps , Asanka Amarasinghe , Philip D. Mannheim
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