Abstract: In this article, we initiate our exploration with a time-varying optimization problem, featuring linear equality constraints. To address this complex problem, we introduce a novel continuous ...

Abstract: This article focuses on optimal control problem for a class of discrete-time nonlinear systems. In practical applications, computation time is a crucial consideration when solving optimal ...

This repository contains the official code for the paper MARS: Unleashing the Power of Variance Reduction for Training Large Models.

This repository contains an implementation of symmetry-adapted Gaussian Process Regression suitable to perform equivariant learning and prediction of the electron density of molecular and ...

A gradient preconditioning approach based on transmitted wave energy for least-squares reverse time migration (LSRTM) is proposed in this study. The gradient is preconditioned by using the energy of ...

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...