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The same concept can mean different things or be instantiated in different forms depending on context, suggesting a degree of flexibility within the conceptual system. We propose that a compositional network model can be used to capture and…

Neurons and Cognition · Quantitative Biology 2019-03-21 Sarah H. Solomon , John D. Medaglia , Sharon L. Thompson-Schill

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

In this paper, we present and analyze a new mixed finite element formulation of a general family of quasi-static multiple-network poroelasticity (MPET) equations. The MPET equations describe flow and deformation in an elastic porous medium…

Numerical Analysis · Mathematics 2018-04-23 Jeonghun J. Lee , Eleonora Piersanti , Kent-Andre Mardal , Marie E. Rognes

We propose a splitting algorithm for solving a system of composite monotone inclusions formulated in the form of the extended set of solutions in real Hilbert spaces. The resluting algorithm is a an extension of the algorithm in [4]. The…

Optimization and Control · Mathematics 2013-08-14 Dinh Dung , Bang Cong Vu

The Hopfield network serves as a fundamental energy-based model in machine learning, capturing memory retrieval dynamics through an ordinary differential equation (ODE). The model's output, the equilibrium point of the ODE, is traditionally…

Machine Learning · Computer Science 2024-08-22 Cédric Goemaere , Johannes Deleu , Thomas Demeester

A class of finite-state and discrete-time optimal control problems is introduced. The problems involve a large number of agents with independent dynamics, which interact through an aggregative term in the cost function. The problems are…

Optimization and Control · Mathematics 2023-07-10 Kang Liu , Nadia Oudjane , Laurent Pfeiffer

We study operator-splitting schemes for approximating Koopman generators of linear semigroups induced by nonlinear flows, a framework originating with Dorroh and Neuberger. Building on ideas of Lie, Kowalewski, and Gr\"{o}bner, we analyze…

Numerical Analysis · Mathematics 2025-12-17 A. Banjara , I. AlJabea , T. Papamarkou , F. Neubrander

Numerical computation of the ideal Magnetohydrodynamic (MHD) equilibrium magnetic field is at the base of stellarator optimisation and provides the starting point for solving more sophisticated Partial Differential Equations (PDEs) like…

Plasma Physics · Physics 2026-04-15 Timo Thun , Rory Conlin , Dario Panici , Daniel Böckenhoff

An efficient nonlinear multigrid method for a mixed finite element method of the Darcy-Forchheimer model is constructed in this paper. A Peaceman-Rachford type iteration is used as a smoother to decouple the nonlinearity from the divergence…

Numerical Analysis · Mathematics 2017-04-27 Jian Huang , Long Chen , Hongxing Rui

Lambert's problem has been long studied in the context of space operations; its solution enables accurate orbit determination and spacecraft guidance. This work offers an analytical solution to Lambert's problem using the Koopman Operator…

Numerical Analysis · Mathematics 2022-12-06 Julia Pasiecznik , Simone Servadio , Richard Linares

Robin Hirsch posed in 1996 the 'Really Big Complexity Problem': classify the computational complexity of the network satisfaction problem for all finite relation algebras A. We provide a complete classification for the case that A is…

Logic · Mathematics 2023-01-06 Manuel Bodirsky , Simon Knäuer

Non-overlapping Schwarz methods with generalized Robin transmission conditions were originally introduced by B. Despr\'es for time-harmonic wave propagation problems and have largely developed over the past thirty years. The aim of the…

Numerical Analysis · Mathematics 2022-04-08 Clemens Pechstein

We propose a simple yet effective wireless network coding and decoding technique for a multiple unicast network. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by…

Information Theory · Computer Science 2012-09-06 Tugcan Aktas , A. Ozgur Yilmaz , Emre Aktas

We develop a system-theoretic framework for the structured analysis of distributed optimization algorithms with decomposable cost functions. We model such algorithms as a network of interacting dynamical systems and derive tests for…

Optimization and Control · Mathematics 2026-04-14 Aron Karakai , Jaap Eising , Andrea Martinelli , Florian Dörfler

We propose an explicit construction of Poincar\'e operators for the lowest order finite element spaces, by employing spanning trees in the grid. In turn, a stable decomposition of the discrete spaces is derived that leads to an efficient…

Numerical Analysis · Mathematics 2024-10-14 Wietse M. Boon

An operator algebra implementation of Markov chain Monte Carlo algorithms for simulating Markov random fields is proposed. It allows the dynamics of networks whose nodes have discrete state spaces to be specified by the action of an update…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Stephen Luttrell

By exploiting the superiority of non-orthogonal multiple access (NOMA), NOMA-aided mobile edge computing (MEC) can provide scalable and low-latency computing services for the Internet of Things. However, given the prevalent stochasticity of…

Information Theory · Computer Science 2021-07-01 Meihui Hua , Hui Tian , Xinchen Lyu , Wanli Ni , Gaofeng Nie

This paper presents SIMPOL (Simplified Policy Iteration), a modular numerical framework for solving continuous-time heterogeneous agent models. The core economic problem, the optimization of consumption and savings under idiosyncratic…

Computational Finance · Quantitative Finance 2025-09-30 Ricardo Alonzo Fernández Salguero

We consider the problem of solving mixed random linear equations with $k$ components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels…

Machine Learning · Computer Science 2016-08-23 Xinyang Yi , Constantine Caramanis , Sujay Sanghavi

In this paper, we consider the problem of distributed optimisation of a separable convex cost function over a graph, where every edge and node in the graph could carry both linear equality and/or inequality constraints. We show how to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-20 Richard Heusdens , Guoqiang Zhang