DiffSharp: Automatic Differentiation Library
DiffSharp is an automatic differentiation (AD) library. AD allows exact and efficient calculation of derivatives, by systematically invoking the chain rule of calculus at the elementary operator level during program execution. AD is different from numerical differentiation, which is prone to... More information
FsAlg: Generic Linear Algebra Library
FsAlg is a linear algebra library that supports generic types. It is implemented in the F# language. The library provides generic Vector and Matrix types that support most of the commonly used linear algebra operations, including matrix–vector operations, matrix inverse, determinants, eigenvalues,... More information
Hype: Compositional Machine Learning and Hyperparameter Optimization
Hype is a proof-of-concept deep learning library, where you can perform optimization on compositional machine learning systems of many components, even when such components themselves internally perform optimization. This is enabled by nested automatic differentiation (AD) giving you access to the... More information