Am I missing something? I have never seen a GitHub project with math notation in the README, and I can't think of a case where that would be useful. The more general problem of adding math notation to markdown is worth considering. It's painful to read blog posts that include a lot of math (for example, anything written by John Baez).
There are already several extensions to markdown with LaTeX support. For example, StackExchange supports flavored markdown with a Mathjax backend, as do most static Markdown renderers out there. Nevertheless, since Markdown isn't standardized across the field, we really can't complain that some support LaTeX while others do not. Since it gets asked about in /github/markdown often enough however, I believe that it's worth some consideration.
I think the answer to your question is more situational. For example, the ML community routinely publish supplementary material on Github. While the introductory section of these repositories should be accessible to everyone, they do also go fairly deep with technicals before referencing their respective publication for more details. The PL community also routinely use Github as a distribution platform. For them, it's often much more compact to give the semantics of their language-extension as a system of equations rather than as words. This doesn't absolve them of the obligation of giving readable examples of the specification, but for some of these more technical repositories, it's a nice-to-have as well.
Having said all of this, the ML community has thought up of a rather clever workaround for this already. Github renders ipynb notebooks that has LaTeX in side of its Markdown sections, so many READMEs just reference a Jupyter notebook. This is just a different approach on that problem.
chmaynard|9 years ago
leegao|9 years ago
I think the answer to your question is more situational. For example, the ML community routinely publish supplementary material on Github. While the introductory section of these repositories should be accessible to everyone, they do also go fairly deep with technicals before referencing their respective publication for more details. The PL community also routinely use Github as a distribution platform. For them, it's often much more compact to give the semantics of their language-extension as a system of equations rather than as words. This doesn't absolve them of the obligation of giving readable examples of the specification, but for some of these more technical repositories, it's a nice-to-have as well.
Having said all of this, the ML community has thought up of a rather clever workaround for this already. Github renders ipynb notebooks that has LaTeX in side of its Markdown sections, so many READMEs just reference a Jupyter notebook. This is just a different approach on that problem.