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We present the first near optimal approximation schemes for the maximum weighted (uncapacitated or capacitated) $b$--matching problems for non-bipartite graphs that run in time (near) linear in the number of edges. For any…

Data Structures and Algorithms · Computer Science 2018-06-19 Kook Jin Ahn , Sudipto Guha

In this article we develop a new methodology to prove weak approximation results for general stochastic differential equations. Instead of using a partial differential equation approach as is usually done for diffusions, the approach…

Probability · Mathematics 2016-08-16 Emmanuelle Clément , Arturo Kohatsu-Higa , Damien Lamberton

We prove the well-posedness of entropy solutions for a wide class of nonlocal transport equations with nonlinear mobility in one spatial dimension. The solution is obtained as the limit of approximations constructed via a deterministic…

Analysis of PDEs · Mathematics 2025-09-25 Simone Fagioli , Oliver Tse

We present a method to linearize, without approximation, a specific class of eigenvalue problems with eigenvector nonlinearities (NEPv), where the nonlinearities are expressed by scalar functions that are defined by a quotient of linear…

Numerical Analysis · Mathematics 2021-05-24 Rob Claes , Elias Jarlebring , Karl Meerbergen , Parikshit Upadhyaya

This paper gives the existence and uniqueness results for solution of fractional differential equations with Hilfer derivative. Using some new techniques and generalizing the restrictive conditions imposed on considered function, the…

Classical Analysis and ODEs · Mathematics 2017-09-29 D. B. Dhaigude , Sandeep P. Bhairat

A method is introduced for the construction of meshless discretization schemes which preserve Lie symmetries of the differential equations that these schemes approximate. The method exploits the fact that equivariant moving frames provide a…

Mathematical Physics · Physics 2015-06-11 Alexander Bihlo

We introduce a generalized finite difference method for solving a large range of fully nonlinear elliptic partial differential equations in three dimensions. Methods are based on Cartesian grids, augmented by additional points carefully…

Numerical Analysis · Mathematics 2021-03-19 Brittany Froese Hamfeldt , Jacob Lesniewski

In this paper, it is shown how a combination of approximate symmetries of a nonlinear wave equation with small dissipations and singularity analysis provides exact analytic solutions. We perform the analysis using the Lie symmetry algebra…

Mathematical Physics · Physics 2019-09-24 Alfred Michel Grundland , Alexander Hariton

New problem is considered that is to find nonlinear differential equations with special solutions. Method is presented to construct nonlinear ordinary differential equations with exact solution. Crucial step to the method is the assumption…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 N. A. Kudryashov

It is well recognized that new types of exact travelling wave solutions to nonlinear partial differential equations can be obtained by modifications of the methods which are in hand. In this study, we extend the class of auxiliary equations…

Mathematical Physics · Physics 2015-12-15 Zehra Pinar , Turgut Ozis

The perimeter and area generating functions of exactly solvable polygon models satisfy q-functional equations, where q is the area variable. The behaviour in the vicinity of the point where the perimeter generating function diverges can…

Statistical Mechanics · Physics 2008-08-28 C. Richard , A. J. Guttmann

We apply the semi-discrete method, c.f. \emph{N. Halidias and I.S. Stamatiou (2016), On the numerical solution of some non-linear stochastic differential equations using the semi-discrete method, Computational Methods in Applied…

Numerical Analysis · Mathematics 2018-07-25 Ioannis S. Stamatiou

High-dimensional partial differential equations (PDE) appear in a number of models from the financial industry, such as in derivative pricing models, credit valuation adjustment (CVA) models, or portfolio optimization models. The PDEs in…

Numerical Analysis · Mathematics 2020-07-15 Christian Beck , Weinan E , Arnulf Jentzen

We suggest the method for group classification of evolution equations admitting nonlocal symmetries which are associated with a given evolution equation possessing nontrivial Lie symmetry. We apply this method to second-order evolution…

Exactly Solvable and Integrable Systems · Physics 2009-07-13 Renat Zhdanov

Most of the existing methods for estimating the local intrinsic dimension of a data distribution do not scale well to high-dimensional data. Many of them rely on a non-parametric nearest neighbors approach which suffers from the curse of…

We present a nonlinear dynamical approximation method for time-dependent Partial Differential Equations (PDEs). The approach makes use of parametrized decoder functions, and provides a general, and principled way of understanding and…

Numerical Analysis · Mathematics 2025-05-20 Daan Bon , Benjamin Caris , Olga Mula

Generalized linear models and the quasi-likelihood method extend the ordinary regression models to accommodate more general conditional distributions of the response. Nonparametric methods need no explicit parametric specification, and the…

Statistics Theory · Mathematics 2009-11-23 Jianqing Fan , Yichao Wu , Yang Feng

In this paper, we propose an approach for computing invariant sets of discrete-time nonlinear systems by lifting the nonlinear dynamics into a higher dimensional linear model. In particular, we focus on the \emph{maximal admissible…

Systems and Control · Electrical Eng. & Systems 2022-07-22 Zheming Wang , Raphaël M. Jungers , Chong-Jin Ong

Recently, it has been great interest in the development of methods for solving nonlinear differential equations directly. Here, it is shown an algorithm based on Pad\'e approximants for solving nonlinear partial differential equations…

Mathematical Physics · Physics 2015-01-28 Danilo V. Ruy

The neural network-based approach to solving partial differential equations has attracted considerable attention due to its simplicity and flexibility in representing the solution of the partial differential equation. In training a neural…

Machine Learning · Computer Science 2022-01-10 Jihun Han , Yoonsang Lee
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