I'm a PhD student in the Machine Learning group in Cambridge.
I primarily work on Gaussian processes -- how to scale them to large data sets, how to use them in climate science, and how best to write software that implements them.
Any time you want to fit a model you have to figure out how to manage its parameters, and how to work with standard optimisation and inference interfaces.
This becomes complicated for all but the most trivial models.
ParameterHandling.jl provides an API and tooling to help you manage this complexity in a scalable way.
We'll show how you might use ParameterHandling.jl, how to extend it, and how it relates to other tools.