[POT] Wasserstein Barycenters for more than 1-D distributions

Hi, Thanks for a great tool box. In the example as well in documentation – the method ot.bregman.barycenter(A,M..) calculates the entropic regularized wasserstein barycenter of distributions A where each column of A is considered a distribution implying – that it computes Barycenters for 1-D distributions. I want to ask if there is an easy way to extend this to more than 1-D distributions, say 2 or 3 or to arbitrary dimensions. I have read the convolutional Wasserstein distance paper by Solomon et al (SIGGRAPH 2015). I also want to ask if it will be implemented in this toolbox as well? Thanks Kowshik Thopalli