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).

Work in progress..

Support:

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

Todo:

• Extend from scalar to multidimensional entities, with Ricci calculus for manipulating tensors and doing derivatives
• more ops and tests (see src/core.rs)

Other:

• currently depends on Rust nightly