Interpretable Probabilistic Embeddings: Bridging the Gap Between Topic Models and Neural Networks
Crossref DOI link: https://doi.org/10.1007/978-3-319-71746-3_15
Published Online: 2017-11-28
Published Print: 2018
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Potapenko, Anna
Popov, Artem
Vorontsov, Konstantin
License valid from 2017-11-28