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Learning the distance metric between pairs of samples has been studied for image retrieval and clustering. With the remarkable success of pair-based metric learning losses, recent works have proposed the use of generated synthetic points on…

Computer Vision and Pattern Recognition · Computer Science 2020-04-24 Byungsoo Ko , Geonmo Gu

We consider the equilibrium equations for a linearized Cosserat material and provide two perspectives concerning well-posedness. First, the system can be viewed as the Hodge Laplace problem on a differential complex. On the other hand, we…

Numerical Analysis · Mathematics 2024-10-22 Wietse Marijn Boon , Omar Duran , Jan Martin Nordbotten

For difference variational problems on lattice, this paper presents a relation between divergence variational symmetries and conservation laws for the associated Euler-Lagrange system provided by Noether's theorem. This hence inspires us to…

Mathematical Physics · Physics 2019-07-08 Linyu Peng

We use the general framework of summation-by-parts operators to construct conservative, energy-stable, and well-balanced semidiscretizations of two different nonlinear systems of dispersive shallow water equations with varying bathymetry:…

Numerical Analysis · Mathematics 2025-11-12 Joshua Lampert , Hendrik Ranocha

In this paper, we highlight the complimentary nature of the results of Anco & Bluman and Ibragimov in the construction of conservation laws; that whilst the former establishes the role of multipliers, the latter presents a formal procedure…

Analysis of PDEs · Mathematics 2018-10-24 A H Kara

Energy preserving numerical methods for a certain class of PDEs are derived, applying the partition of unity method. The methods are extended to also be applicable in combination with moving mesh methods by the rezoning approach. These…

Numerical Analysis · Mathematics 2017-10-04 Sølve Eidnes , Torbjørn Ringholm

Kahan's method and a two-step generalization of the discrete gradient method are both linearly implicit methods that can preserve a modified energy for Hamiltonian systems with a cubic Hamiltonian. These methods are here investigated and…

Numerical Analysis · Mathematics 2020-05-11 Sølve Eidnes , Lu Li , Shun Sato

In recent years, a significant amount of attention has been paid to solve partial differential equations (PDEs) by deep learning. For example, deep Galerkin method (DGM) uses the PDE residual in the least-squares sense as the loss function…

Numerical Analysis · Mathematics 2020-06-09 Liyao Lyu , Zhen Zhang , Minxin Chen , Jingrun Chen

The fundamental idea of embedding a network in a metric space is rooted in the principle of proximity preservation. Nodes are mapped into points of the space with pairwise distance that reflects their proximity in the network. Popular…

Physics and Society · Physics 2021-01-15 Yi-Jiao Zhang , Kai-Cheng Yang , Filippo Radicchi

In the classical Lagrangian approach to conservation laws of gauge-natural field theories a suitable (vector) density is known to generate the so--called {\em conserved Noether currents}. It turns out that along any section of the relevant…

Mathematical Physics · Physics 2010-12-03 L. Fatibene , M. Francaviglia , M. Palese

In this dissertation we study basic local differential geometry, projective differential geometry, and prolongations of overdetermined geometric partial differential equations. It is simple to prolong an n-th order linear ordinary…

Differential Geometry · Mathematics 2024-05-27 Jake McNaughton

In this paper, a general theorem on the equivalence of pth moment stability between stochastic differential delay equations (SDDEs) and their numerical methods is proved under the assumptions that the numerical methods are strongly…

Numerical Analysis · Mathematics 2019-07-31 Zhenyu Bao , Jingwen Tang , Yan Shen , Wei Liu

Reduced basis methods are popular for approximately solving large and complex systems of differential equations. However, conventional reduced basis methods do not generally preserve conservation laws and symmetries of the full order model.…

Numerical Analysis · Mathematics 2018-03-20 Babak Maboudi Afkham , Jan S. Hesthaven

We present and analyze a new embedded--hybridized discontinuous Galerkin finite element method for the Stokes problem. The method has the attractive properties of full hybridized methods, namely an $H({\rm div})$-conforming velocity field,…

Numerical Analysis · Mathematics 2023-07-06 Sander Rhebergen , Garth N. Wells

This paper presents identification of both network connected systems as well as distributed systems governed by PDEs in the framework of distributed optimization via the Alternating Direction Method of Multipliers. This approach opens first…

Systems and Control · Computer Science 2014-03-20 Anders Hansson , Michel Verhaegen

Learning distributed representations for nodes in graphs is a crucial primitive in network analysis with a wide spectrum of applications. Linear graph embedding methods learn such representations by optimizing the likelihood of both…

Machine Learning · Computer Science 2018-10-16 Yihan Gao , Chao Zhang , Jian Peng , Aditya Parameswaran

Symmetry properties of conservation laws of partial differential equations are developed by using the general method of conservation law multipliers. As main results, simple conditions are given for characterizing when a conservation law…

Mathematical Physics · Physics 2016-12-21 Stephen C. Anco

In Ref.~\cite{Sag} we proposed a geometric formulation of generalized Nambu mechanics. In the present paper we extend the class of Nambu systems by replacing the stringent condition of constancy of 3-form by closedness. We also explore the…

Dynamical Systems · Mathematics 2007-05-23 Sagar A. Pandit , Anil D. Gangal

A discrete analogue of the dressing method is presented and used to derive integrable nonlinear evolution equations, including two infinite families of novel continuous and discrete coupled integrable systems of equations of nonlinear…

Exactly Solvable and Integrable Systems · Physics 2018-10-18 Gino Biondini , Qiao Wang

We introduce a new approach for designing numerical schemes for stochastic differential equations (SDEs). The approach, which we have called direction and norm decomposition method, proposes to approximate the required solution $X_t$ by…

Numerical Analysis · Mathematics 2017-02-21 C. M. Mora , H. A. Mardones , J. C. Jimenez , M. Selva , R. Biscay