Vouivre
A dependent type system for machine learning in Lisp
Current machine learning frameworks are built around relatively weak type systems. This is a problem because, at scale, machine learning applications are exceedingly intricate and computationally expensive, therefore making costly runtime errors unavoidable. This is where Vouivre comes into play. Using a dependent-type system, the project aims at enabling users to write machine-learning applications that solve real-world problems with compile-time validation of their correctness, thus preventing runtime errors at a reasonable computational cost.
- The project's own website: https://vouivredigital.com
This project was funded through the NGI0 Core Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 101092990.
