# NeuralPDE.jl: Scientific Machine Learning for Partial Differential Equations

NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learning (SciML) techniques such as physics-informed neural networks (PINNs) and deep BSDE solvers. This package utilizes deep neural networks and neural stochastic differential equations to solve high-dimensional PDEs at a greatly reduced cost and greatly increased generality compared with classical methods.

## Features

• Physics-Informed Neural Networks for automated PDE solving
• Forward-Backwards Stochastic Differential Equation (FBSDE) methods for parabolic PDEs
• Deep-learning-based solvers for optimal stopping time and Kolmogorov backwards equations

## Citation

@article{zubov2021neuralpde,
}