Open access
Oct 2026
Posterior sampling of word embeddings
We study Bayesian inference for probabilistic word embedding models, including skip-gram with negative sampling (SGNS) and continuous bag-of-words (CBoW). These models are widely used for inference, but their posteriors are non-identifiable under general linear transformations, which prevents meaningful Bayesian uncert...
Väinö Yrjänäinen, Isac Boström, Johan Jonasson et al.
· Statistics and computing · 0 citations