Show HN: Jixp – Lisp DSL for Defining Jax Neural Networks

Show HN introduces Jixp, a new Lisp‑style DSL aimed at Jax users. The language lets developers write neural‑network architectures in a compact syntax. Jixp translates the Lisp expressions into Jax‑compatible code automatically. It targets researchers who prefer functional programming paradigms. The project is hosted on GitHub and includes examples and documentation. Early feedback highlights easier experimentation compared with raw Jax code. The DSL supports common layers, activation functions, and parameter initialization. Community members are invited to contribute enhancements or report issues.