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 ...

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

Abstract: For linear time-invariant systems, the design of an optimal controller is a commonly encountered problem in many applications. Among all the optimization approaches available, the linear ...

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 ...

Structure-property relations of granular materials are governed by the arrangement of particles and the chains of forces between them. These relations enable design of wave damping materials and ...