slicer provides functions for computing sliced Wasserstein distances as well as one-dimensional Wasserstein distances between empirical distributions represented as matrices. The distances can be fed to a kernel function (currently, only the Gaussian radial basis function kernel is supported), which can then be used in a Gaussian process regression model.