Hello!!
I’m pleased to announce the package BayesianTomography.jl. As the name suggests, its aim is to perform Quantum State Tomography using Bayesian inference.
The basic ideia is that the outcomes of a quantum experiment define a posterior distribution in the space of quantum states. Then, in a certain sense, the best possible point prediction for the state that produced our results is the mean of this posterior. We utilize a Metropolis Adjusted Langevin Algorithm (MALA) to perform the sampling.
I have also written a documentation explaining the usage of the package. The basic usage can be seen here. There is also a section explaining the theory (there is a nice animation there, go check it out 
). We also expose the docstrings of every defined function.
I hope you find this package useful. Any doubts/suggestions/contributions are extremely welcome!