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  "Title": "Topic Modelling in Embedding Spaces",
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  "Description": "Find topics in texts which are semantically embedded using\ntechniques like word2vec or Glove. This topic modelling\ntechnique models each word with a categorical distribution\nwhose natural parameter is the inner product between a word\nembedding and an embedding of its assigned topic. The\ntechniques are explained in detail in the paper 'Topic Modeling\nin Embedding Spaces' by Adji B. Dieng, Francisco J. R. Ruiz,\nDavid M. Blei (2019), available at\n<doi:10.48550/arXiv.1907.04907>.",
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