Meta-embeddings are a probabilistic generalization of embeddings in machine learning. This project started at the 2017 JHU HLTCOE SCALE Workshop.
For now, all the action is theoretical and happening via the collaborative writing of a document. See theory folder.
There is already some MATLAB code to demonstrate Gaussian meta-embeddings. This code is now being used to generate some examples in the document.