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Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks

Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks

Anna Potapenko
Artem Popov
K. Vorontsov
    BDL
ArXiv (abs)PDFHTML

Papers citing "Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks"

1 / 1 papers shown
Title
Mixing syntagmatic and paradigmatic information for concept detection
Mixing syntagmatic and paradigmatic information for concept detection
L. Chartrand
Mohamed Bouguessa
20
2
0
09 Apr 2019

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