Sppmi Svd

Implementation of "Neural Word Embedding as Implicit Matrix Factorization"
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Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
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4 years agomitPython
utility class for building/evaluating document representations
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2 years agogpl-3.0Python
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Hpca29
7 years ago1gpl-3.0C
C++ implementation of the Hellinger PCA for computing word embeddings.
Cmdist22
3 years agogpl-3.0R
DEPRECATED - The Concept Mover's Distance Method is now available in the text2map package. Concept Mover's Distance measure a document's conceptual engagement using word embeddings.
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4 years agoPython
TensorFlow implementation of word2vec
Sppmi Svd10
2 years ago3Python
Implementation of "Neural Word Embedding as Implicit Matrix Factorization"
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5 years agoR
This repository implements models described in ''Interpretale Word Embeddings via Informative Priors''
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5 years agoC
We use principal component analysis for word embedding. The method is able to process both annotated and raw corpora.
Text_embedding6
5 years ago7Python
Inferring vector of unseen words
Matrix Benchmark6
3 years agomitPython
A cupy (GPU) / numpy benchmark to measure how fast different hardware can perform matrix operations.
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Python
Natural Language Processing
Matrix
Word Embeddings
Svd
Matrix Factorization