gdalle | 10 months ago | on: An illustrated guide to automatic sparse differentiation
Indeed, CasADi is among the precursors in this area! The key difference with our approach is their use of a domain-specific language, with distinct mathematical functions and array types. This has lots of benefits, but it expects users to rewrite their existing code in the CasADi formalism.
What we seek to achieve in Julia is compatibility with native code, without a DSL-imposed refactor. We share this ambition with the broader Julia autodiff ecosystem, which is focused on differentiating the language as a whole. Of course it doesn't always work, but in many cases, it enables a plug-and-play approach to (sparse) autodiff which makes really cool applications possible.