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
Categories
Data VisualizationLicense
MIT LicenseFollow ImplicitDifferentiation.jl
Other Useful Business Software
Host LLMs in Production With On-Demand GPUs
Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of ImplicitDifferentiation.jl!