Download
ImplicitDifferentiation.jl is a package for automatic differentiation of functions defined implicitly, i.e., forward mappings. Those for which automatic differentiation fails. Reasons can vary depending on your backend, but the most common include calls to external solvers, mutating operations or type restrictions. Those for which automatic differentiation is very slow. A common example is iterative procedures like fixed point equations or optimization algorithms.
Features
- Package for automatic differentiation of functions defined implicitly
- Documentation available
- Examples available
- Licensed under the MIT License
- Automatic differentiation of implicit functions
Project Samples
Categories
Data VisualizationLicense
MIT LicenseFollow ImplicitDifferentiation.jl
Other Useful Business Software
Train ML Models With SQL You Already Know
Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of ImplicitDifferentiation.jl!
