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With the ever increasing computational power available and the development of high-performances computing, investigating the properties of realistic very large-scale nonlinear dynamical systems has been become reachable. It must be noted…

In this paper we address the question of whether it is possible to integrate time-dependent high-dimensional PDEs with hierarchical tensor methods and explicit time stepping schemes. To this end, we develop sufficient conditions for…

Numerical Analysis · Mathematics 2020-03-18 Abram Rodgers , Daniele Venturi

We show that accelerated gradient descent, averaged gradient descent and the heavy-ball method for non-strongly-convex problems may be reformulated as constant parameter second-order difference equation algorithms, where stability of the…

Machine Learning · Statistics 2015-04-08 Nicolas Flammarion , Francis Bach

The matter of the stability for multi-asset American option pricing problems is a present remaining challenge. In this paper a general transformation of variables allows to remove cross derivative terms reducing the stencil of the proposed…

Pricing of Securities · Quantitative Finance 2017-01-31 Rafael Company , Vera Egorova , Lucas Jódar , Fazlollah Soleymani

In this paper, we introduce a data-driven modeling approach for dynamics problems with latent variables. The state-space of the proposed model includes artificial latent variables, in addition to observed variables that can be fitted to a…

Optimization and Control · Mathematics 2024-06-19 Yushuang Luo , Xiantao Li , Wenrui Hao

In this paper, the stability behaviors of stochastic differential equations (SDEs) driven by time-changed Brownian motions are discussed. Based on the generalized Lyapunov method and stochastic analysis, necessary conditions are provided…

Probability · Mathematics 2016-02-29 Qiong Wu

The phase-field crystal equation, a parabolic, sixth-order and nonlinear partial differential equation, has generated considerable interest as a possible solution to problems arising in molecular dynamics. This is because the phase-field…

Mathematical Physics · Physics 2015-07-29 Philippe Vignal , Lisandro Dalcin , Donald L. Brown , Nathan Collier , Victor M. Calo

Nonlinear differential equations rarely admit closed-form solutions, thus requiring numerical time-stepping algorithms to approximate solutions. Further, many systems characterized by multiscale physics exhibit dynamics over a vast range of…

Machine Learning · Computer Science 2020-08-26 Yuying Liu , J. Nathan Kutz , Steven L. Brunton

One of the most popular methods of controlling dynamical systems is feedback. It can be used without acquiring detailed knowledge of the underlying system. In this work, we study the stability of fractional-order linear difference equations…

Dynamical Systems · Mathematics 2023-04-26 Divya D. Joshi , Sachin Bhalekar , Prashant M. Gade

Differential equations are frequently used in engineering domains, such as modeling and control of industrial systems, where safety and performance guarantees are of paramount importance. Traditional physics-based modeling approaches…

Systems and Control · Electrical Eng. & Systems 2020-11-30 Aaron Tuor , Jan Drgona , Draguna Vrabie

In this work, we numerically study linear stability of multiple steady-state solutions to a type of steric Poisson--Nernst--Planck (PNP) equations with Dirichlet boundary conditions, which are applicable to ion channels. With numerically…

Computational Physics · Physics 2020-12-02 Jie Ding , Hui Sun , Shenggao Zhou

In this paper, we study the "stability" of machine learning (ML) models within the context of larger, complex NLP systems with continuous training data updates. For this study, we propose a methodology for the assessment of model stability…

Computation and Language · Computer Science 2022-01-19 Huiting Liu , Avinesh P. V. S. , Siddharth Patwardhan , Peter Grasch , Sachin Agarwal

In this paper we study the continuous dependence with respect to obstacles for obstacle problems with measure data. This is deeply investigated introducing a suitable type of convergence, which gives stability under very general hypotheses.…

Functional Analysis · Mathematics 2007-05-23 Paolo Dall'Aglio

Forecasting physical signals in long time range is among the most challenging tasks in Partial Differential Equations (PDEs) research. To circumvent limitations of traditional solvers, many different Deep Learning methods have been…

Machine Learning · Computer Science 2023-06-09 Leon Migus , Julien Salomon , Patrick Gallinari

Kinetic equations model distributions of particles in position-velocity phase space. Often, one is interested in studying the long-time behavior of particles in high-collisional regimes in which an approximate (advection)-diffusion model…

Numerical Analysis · Mathematics 2021-07-09 Emil Løvbak , Giovanni Samaey , Stefan Vandewalle

A posteriori error estimates based on residuals can be used for reliable error control of numerical methods. Here, we consider them in the context of ordinary differential equations and Runge-Kutta methods. In particular, we take the…

Numerical Analysis · Mathematics 2024-09-25 Hendrik Ranocha , Jan Giesselmann

The purpose of this paper is to introduce a new Kirk type iterative algorithm called Kirk multistep iteration and to study its convergence. We also prove some theorems related with the stability results for the Kirk-multistep and Kirk-SP…

Functional Analysis · Mathematics 2013-06-11 Faik Gürsoy , Vatan Karakaya , B. E. Rhoades

In this work characterizations of notions of output stability for uncertain time-varying systems described by retarded functional differential equations are provided. Particularly, characterizations by means of Lyapunov and Razumikhin…

Optimization and Control · Mathematics 2007-05-23 Iasson Karafyllis , Pierdomenico Pepe , Zhong-Ping Jiang

We study the notion of stochastic stability with respect to diffusive perturbations for flows with smooth invariant measures. We investigate the question fully for non-singular flows on the circle. We also show that volume-preserving flows…

Dynamical Systems · Mathematics 2011-12-02 Sergiu Aizicovici , Todd Young

Methods for the reduction of the complexity of computational problems are presented, as well as their connections to renormalization, scaling, and irreversible statistical mechanics. Several statistically stationary cases are analyzed; for…

Numerical Analysis · Mathematics 2007-05-23 Alexandre J. Chorin , Panagiotis Stinis