friedrich VS Peroxide

For other algorithms, there is not yet a single library to rule them all (linfa might become that at some point) but searching for the algorithm you need on crate.io is likely to give you some results (obligatory plug to Friedrich, my gaussian process implementation).

For me the good reason to use gaussian regression is the fact that you get an uncertainty on the output.

The big downside is that it takes expert knowledge (to design a proper kernel) and a solid implementation (to avoid the various numerical problems they can produce) to apply them to practical problem. Most implementation either break down very quickly or are not flexible enough for my taste.

I have a Rust implementation [0] which tries to help with the flexibility aspect but it is still very far from perfect.

[0]: https://github.com/nestordemeure/friedrich

Rust’s standard library is relatively small by design and doesn’t contain any tools for numeric integration. However, you can probably find a crate on crates.io that does what you need. A quick search suggests Peroxide.

peroxide seems really cool, but I haven't had the opportunity to use it much yet.

peroxide covers some of this area. It could work as a starting point for something in the ML or probabilistic programming domains.