Dynamic Automatic Differentiation in Rust

A pedagogical attempt at auto-differentiation. This is based on the autograd package and other variations of it as well as literature references (eg: The Art of Differentiating Computer Programs, An Introduction to Algorithmic Differentiation – Uwe Naumann).

Support:

• forward mode
• reverse mode
• a composition thereof for higher-order derivatives.

Todo:

• Multidimension support, possibly with help of ndarray crate
• Add support for Ricci calculus notation for symbolic manipulation (reference: Computing Higher Order Derivatives of Matrix and Tensor Expressions by Laue et al.)
• More ops and tests (see src/core.rs)

Plots:

<p align="center"> <img src="images/eg_simple_plot_tan.png" alt="drawing" width="400"/> <img src="images/eg_simple_plot_sin.png" alt="drawing" width="400"/> </p>