Download
NeuralPDE.jl is a Julia library for solving partial differential equations (PDEs) using physics-informed neural networks and scientific machine learning. Built on top of the SciML ecosystem, it provides a flexible and composable interface for defining PDEs and training neural networks to approximate their solutions. NeuralPDE.jl enables hybrid modeling, data-driven discovery, and fast PDE solvers in high dimensions, making it suitable for scientific research and engineering applications.
Features
- Solves PDEs using physics-informed neural networks (PINNs)
- Supports symbolic PDE definition via Symbolics.jl
- Integrates with Flux.jl and SciML solvers
- Enables hybrid and data-driven modeling
- Handles high-dimensional and nonlinear systems
- GPU acceleration and automatic differentiation support
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow NeuralPDE.jl
Other Useful Business Software
MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of NeuralPDE.jl!
