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Differential equation discovery, a machine learning subfield, is used to develop interpretable models, particularly in nature-related applications. By expertly incorporating the general parametric form of the equation of motion and…

Machine Learning · Computer Science 2024-02-23 Alexander Hvatov , Roman Titov

We consider a family of singular maps as an example of a simple model of dynamical systems exhibiting the property of robust chaos on a well defined range of parameters. Critical boundaries separating the region of robust chaos from the…

Chaotic Dynamics · Physics 2008-05-20 M. G. Cosenza , O. Alvarez-LLamoza

A critical transition for a system modelled by a concave quadratic scalar ordinary differential equation occurs when a small variation of the coefficients changes dramatically the dynamics, from the existence of an attractor-repeller pair…

Dynamical Systems · Mathematics 2022-11-21 Iacopo P. Longo , Carmen Núñez , Rafael Obaya

We consider the uniqueness of solutions of ordinary differential equations where the coefficients may have singularities. We derive upper bounds on the the order of singularities of the coefficients and provide examples to illustrate the…

Classical Analysis and ODEs · Mathematics 2008-12-19 Yifei Pan , Mei Wang

Differential calculus on discrete sets is developed in the spirit of noncommutative geometry. Any differential algebra on a discrete set can be regarded as a `reduction' of the `universal differential algebra' and this allows a systematic…

High Energy Physics - Theory · Physics 2009-10-28 A. Dimakis , F. Müller-Hoissen

Energy-minimizing constraint maps are a natural extension of the obstacle problem within a vectorial framework. Due to inherent topological constraints, these maps manifest a diverse structure that includes singularities similar to harmonic…

Analysis of PDEs · Mathematics 2024-08-01 Alessio Figalli , André Guerra , Sunghan Kim , Henrik Shahgholian

We investigate the variational structure of discrete Laplace-type equations that are motivated by discrete integrable quad-equations. In particular, we explain why the reality conditions we consider should be all that are reasonable, and we…

Exactly Solvable and Integrable Systems · Physics 2017-04-13 Alexander I. Bobenko , Felix Günther

In materials science, wedge disclinations are defects caused by angular mismatches in the crystallographic lattice. To describe such disclinations, we introduce an atomistic model in planar domains. This model is given by a…

Analysis of PDEs · Mathematics 2020-05-28 Pierluigi Cesana , Patrick van Meurs

Machine learning pipelines often rely on optimization procedures to make discrete decisions (e.g., sorting, picking closest neighbors, or shortest paths). Although these discrete decisions are easily computed, they break the…

Machine Learning · Computer Science 2020-06-11 Quentin Berthet , Mathieu Blondel , Olivier Teboul , Marco Cuturi , Jean-Philippe Vert , Francis Bach

A general sufficient condition for the convergence of subsequences of solutions of non-autonomous, nonlinear difference equations and systems is obtained. For higher order equations the delay sizes and patterns play essential roles in…

Dynamical Systems · Mathematics 2017-07-25 H. Sedaghat

Differential equations where the graph of some derivative of a function is composed of a finite number of similarity transformations of the graph of the function itself are defined. We call these self-similar differential equations (SSDEs)…

Classical Analysis and ODEs · Mathematics 2024-09-17 Leon Q. Brin , Joe Fields

We consider boundary value problems for stochastic differential equations of second order with a small parameter. For this case we prove a special existence and unicity theorem for strong solutions. The asymptotic behavior of these…

Probability · Mathematics 2015-07-08 Mikhail Kamenskii , Marc Quincampoix , Serguei Pergamenchtchikov

A periodic perturbation generates a complicated dynamics close to separatrices and saddle points. We construct an asymptotic solution which is close to the separatrix for the unperturbed Duffing's oscillator over a long time. This solution…

Dynamical Systems · Mathematics 2009-03-27 O. M. Kiselev

We extend two of the methods previously introduced to find discrete symmetries of differential equations to the case of difference and differential-difference equations. As an example of the application of the methods, we construct the…

Mathematical Physics · Physics 2016-08-16 Decio Levi , Miguel A. Rodríguez

The paper deals with systems of ordinary differential equations containing in the right-hand side controls which are discontinuous in phase variables. These controls cause the occurrence of sliding modes. If one uses one of the well-known…

Optimization and Control · Mathematics 2023-05-05 Alexander Fominyh

In this paper we consider discrete gradient methods for approximating the solution and preserving a first integral (also called a constant of motion) of autonomous ordinary differential equations. We prove under mild conditions for a large…

Numerical Analysis · Mathematics 2013-01-22 Richard A. Norton , G. R. W. Quispel

We consider a nonlinear Dirichlet problem driven by a nonhomogeneous differential operator plus an indefinite potential. In the reaction we have the competing effects of a singular term and of concave and convex nonlinearities. In this…

Analysis of PDEs · Mathematics 2020-05-08 Nikolaos S. Papageorgiou , Vicenţiu D. Rădulescu , Dušan D. Repovš

We consider a singularly perturbed problem with mixed Dirichlet and Neumann boundary conditions in a bounded domain $\Omega\subset\R^{n}$ whose boundary has an $(n-2)$-dimensional singularity. Assuming $1<p<\frac{n+2}{n-2}$, we prove that,…

Analysis of PDEs · Mathematics 2012-02-07 Serena Dipierro

Motivated by the study of systems of higher order boundary value problems with functional boundary conditions, we discuss, by topological methods, the solvability of a fairly general class of systems of perturbed Hammerstein integral…

Classical Analysis and ODEs · Mathematics 2021-02-09 Gennaro Infante

We revisit the input perturbations framework for differential privacy where noise is added to the input $A\in \mathcal{S}$ and the result is then projected back to the space of admissible datasets $\mathcal{S}$. Through this framework, we…

Machine Learning · Computer Science 2024-08-09 Vincent Cohen-Addad , Tommaso d'Orsi , Alessandro Epasto , Vahab Mirrokni , Peilin Zhong
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