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Neural ordinary differential equations (Neural ODEs) propose the idea that a sequence of layers in a neural network is just a discretisation of an ODE, and thus can instead be directly modelled by a parameterised ODE. This idea has had…

Machine Learning · Computer Science 2024-05-07 Christina Runkel , Ander Biguri , Carola-Bibiane Schönlieb

Differential Equations are among the most important Mathematical tools used in creating models in the science, engineering, economics, mathematics, physics, aeronautics, astronomy, dynamics, biology, chemistry, medicine, environmental…

History and Overview · Mathematics 2020-12-15 Byakatonda Denis

We present here the General formulation of the problem of existence and construction of upper and lower envelope for an arbitrary function with values from the completion of the ordered set ${\rm S}$ for a certain class of functions with…

Rings and Algebras · Mathematics 2016-03-14 Bulat Khabibullin , Alexei Rozit , Farkhat Khabibullin

In this article we develop the theory of $H$-Orlicz space generated by generalised Young function. Modular convergence of $H$-Orlicz space for the case of vector-valued functions and norm convergence in $\mcH^\theta(X, \bar{\mu})$ where $X$…

Functional Analysis · Mathematics 2022-06-07 Hemanta Kalita , Bipan Hazarika

In this article, firstly we develop a method for a type of difference equations, applicable to solve approximately a class of first order ordinary differential equation systems. In a second step, we apply the results obtained to solve a…

Numerical Analysis · Mathematics 2017-12-12 Fabio Botelho

The standard text book theory of ODEs lacks a general method to solve linear equations having variable coefficients, providing instead a collection of special techniques for particular classes of equations. The present article addresses…

Classical Analysis and ODEs · Mathematics 2025-12-30 Peter C. Gibson

Modifying the moduli of supporting convexity and supporting smoothness, we introduce new moduli for Banach spaces which occur, e.g., as lengths of catheti of right-angled triangles (defined via so-called quasi-orthogonality). These…

Functional Analysis · Mathematics 2017-10-18 Grigiry Ivanov , Horst Martini

Ordinary differential equations (ODEs) and ordinary difference systems (O$\Delta$Ss) invariant under the actions of the Lie groups $\mathrm{SL}_x(2)$, $\mathrm{SL}_y(2)$ and $\mathrm{SL}_x(2)\times\mathrm{SL}_y(2)$ of projective…

Mathematical Physics · Physics 2016-01-20 Rutwig Campoamor-Stursberg , Miguel A. Rodríguez , Pavel Winternitz

From a unified vision of vector valued solutions in weighted Banach spaces, this manuscript establishes the existence and uniqueness for space homogeneous Boltzmann bi-linear systems with conservative collisional forms arising in complex…

Mathematical Physics · Physics 2023-04-13 Ricardo J. Alonso , Irene M. Gamba , Milana Pavic-Colic

In this paper, we classify all simple weight modules with finite-dimensional weight spaces over the $N=2$ Ramond algebra. Any such module $V$ is either a simple highest weight module or a simple lowest weight module, or a simple cuspidal…

Representation Theory · Mathematics 2023-05-31 Dong Liu , Yufeng Pei , Limeng Xia

The method and the formula of variation of constants for ordinary differential equations (ODEs) is a fundamental tool to analyze the dynamics of an ODE near an equilibrium. It is natural to expect that such a formula works for delay…

Dynamical Systems · Mathematics 2023-10-17 Junya Nishiguchi

Classes of Banach spaces that are finitely, strongly finitely or elementary equivalent are introduced. On sets of these classes topologies are defined in such a way that sets of defined classes become compact totally disconnected…

Functional Analysis · Mathematics 2007-05-23 Eugene Tokarev

We consider algebraic ordinary differential equations (AODEs) and study their polynomial and rational solutions. A sufficient condition for an AODE to have a degree bound for its polynomial solutions is presented. An AODE satisfying this…

Symbolic Computation · Computer Science 2018-04-24 Thieu N. Vo , Yi Zhang

We study the theory of ordinary differential equations over a commutative finite dimensional real associative unital algebra $\mathcal{A}$. We call such problems $\mathcal{A}$-ODEs. If a function is real differentiable and its differential…

Rings and Algebras · Mathematics 2017-08-15 Nathan BeDell , James S. Cook

Given a linear ordinary differential equation (ODE) on $\RE$ and a set of interface conditions at a finite set of points $I \subset \RE$, we consider the problem of determining another differential equation whose {\it global} solutions…

Functional Analysis · Mathematics 2019-05-07 Nuno Costa Dias , Cristina Jorge , Joao Nuno Prata

The interpretation of numerical methods, such as finite difference methods for differential equations, as point estimators allows for formal statistical quantification of the error due to discretisation in the numerical context. Competing…

Methodology · Statistics 2018-05-23 Junyang Wang , Jon Cockayne , Chris Oates

A finite-dimensional ${\sf RCD}$ space can be foliated into sufficiently regular leaves, where a differential calculus can be performed. Two important examples are given by the measure-theoretic boundary of the superlevel set of a function…

Functional Analysis · Mathematics 2023-08-24 Emanuele Caputo , Milica Lučić , Enrico Pasqualetto , Ivana Vojnović

The article presents a matrix differential operator and a pseudoinverse matrix differential operator for finding a particular solution to nonhomogeneous linear ordinary differential equations (ODE) with constant coefficients with special…

General Mathematics · Mathematics 2021-01-07 Jozef Fecenko

We give a criterion ensuring that the elementary class of a modular Banach space E (that is, the class of Banach spaces, some ultrapower of which is linearly isometric to an ultrapower of E) consists of all direct sums E\oplus_m H, where H…

Functional Analysis · Mathematics 2017-03-28 C. Ward Henson , Yves Raynaud

We aim to identify the generating, ordinary differential equation (ODE) from a set of trajectories of a partially observed system. Our approach does not need prescribed basis functions to learn the ODE model, but only a rich set of Neural…

Machine Learning · Statistics 2020-03-13 Niklas Heim , Václav Šmídl , Tomáš Pevný