Deep Learning Solution of the Eigenvalue Problem for Differential Operators

no code implementations • 1 Jan 2021 • Ido Ben-Shaul, Leah Bar, Nir Sochen

Solving the eigenvalue problem for differential operators is a common problem in many scientific fields.

Solving the functional Eigen-Problem using Neural Networks

no code implementations • 20 Jul 2020 • Ido Ben-Shaul, Leah Bar, Nir Sochen

In this work, we explore the ability of NN (Neural Networks) to serve as a tool for finding eigen-pairs of ordinary differential equations.

Learning-Based Strong Solutions to Forward and Inverse Problems in PDEs

no code implementations • ICLR Workshop DeepDiffEq 2019 • Leah Bar, Nir Sochen

The solver is grid free, mesh free and shape free, and the solution is approximated by a neural network.

Mesh-Free Unsupervised Learning-Based PDE Solver of Forward and Inverse problems

no code implementations • 25 Sep 2019 • Leah Bar, Nir Sochen

The solver is grid free, mesh free and shape free, and the solution is approximated by a neural network.

Unsupervised Deep Learning Algorithm for PDE-based Forward and Inverse Problems

no code implementations • 10 Apr 2019 • Leah Bar, Nir Sochen

We propose a neural network-based algorithm for solving forward and inverse problems for partial differential equations in unsupervised fashion.