Proposed new feature or change: Numpy provides efficient, vectorized methods for generating random samples of an array with replacement. However, it lacks similar functionality for sampling without ...

One of the simplest and most common techniques for random sampling is to shuffle the data before splitting it into train and test sets. This means that the order of the rows or observations in the ...

I'm currently using a pure-numpy implementation of Annealed Importance Sampling (for binary multivariate RVs), and I'm trying to improve performance by porting the code to jax. I'm benchmarking the ...