Machine learning models are designed to take in data, to find patterns or relationships within those data, and to use what ...

This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis physics-informed neural networks (FBPINNs). To improve the ...

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

1 Mathematics Department, Science Faculty, Karabuk University, Karabük, Türkiye. 2 Faculty of Science Department of Mathematics, Karabuk University, Karabük ...

An illustration of a magnifying glass. An illustration of a magnifying glass.

1 Department of Applied Mathematics, Adama Science and Technology University, Adama, Ethiopia 2 Department of Mathematics, Jimma University, Jimma, Ethiopia In general, the classical numerical methods ...

Abstract: We study boundary-value problems for systems of Hamilton-Jacobi-Bellman first-order partial differential equations and variational inequalities, the solutions of which are constrained to ...

In this article, a new modification of the Adomian decomposition method is performed for the solution fractional order convection–diffusion equation with variable coefficient and initial–boundary ...

Department of Mathematics, Wellesley College, Wellesley, MA, USA. Inhomogenous boundary value problems often occur when an external force is applied to the time evolution of systems governed by ...

The Annals of Applied Probability, Vol. 28, No. 3 (June 2018), pp. 1943-1976 (34 pages) The initial-boundary value problem for the heat equation is solved by using an algorithm based on a random walk ...