This is the Linux app named NeuralPDE.jl whose latest release can be downloaded as v5.20.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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NeuralPDE.jl
DESCRIPTION
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
Programming Language
Julia
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/neuralpde-jl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
