cgravill 

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

Map F# to TypeScript to allow safe interoperability

An FSharp library that can be used while using W#

An FSharp library for the Synthetic Biology Open Language Data Model

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