Abstract: Option pricing, a fundamental problem in finance, often requires solving non-linear partial differential equations (PDEs). When dealing with multi-asset options, such as rainbow options, ...

This repository contains project codes and slides for a mini-lecture designed to introduce neural networks, with a specific application in solving Partial Differential Equations (PDEs). Developed and ...

This repository contains the code necessary to reproduce results from the Bachelor Thesis "Evaluation of Graph Constructions for GNN-Based PDE Solvers", authored by Pavel Khudov Yakovlev. It shows ...

Recently, neural networks have been extensively employed to solve partial differential equations (PDEs) in physical system modeling. While major studies focus on learning system evolution on ...

The remarkable potentials of Artificial Intelligence (AI) and Deep Learning have paved the way for a variety of fields ranging from computer vision and language modeling to healthcare, biology, and ...

Forecasting multivariate time series is a cornerstone for countless applications, ranging from weather prediction to energy consumption management in today’s data-driven world. While effective to a ...