WordGCN
by malllabiisc
ACL 2019: Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks
AI summary
Word embedder
A deep learning model that generates word embeddings by predicting words based on their dependency context
- stars
- 291
- forks
- 64
- watching
- 14
Similar projects
Found by comparing what the projects do, not just their names.
Embedding library
A Common Lisp library for generating word embeddings using neural network models.
Word Embedding Model
A library for training and evaluating a type of word embedding model that extends the original Word2Vec algorithm
Word embeddings
A pre-trained word embedding model informed by a large-scale knowledge graph, providing a nuanced representation of word meanings.
Word embedding model
A Python implementation of a neural network model for learning word embeddings from text data
Sentence Embedder
Provides training and testing code for a CNN-based sentence embedding model
Word embedding generator
This project provides code and corpora for creating word embeddings by considering the visual characteristics of words.
Embeddings
Provides fast and efficient word embeddings for natural language processing.
Word embedding model
A framework to learn word embeddings using lexical dictionaries
Spanish word embeddings
A collection of precomputed word embeddings for the Spanish language, derived from different corpora and computational methods.
Graph Embedder
A sparsity-aware implementation of a deep learning algorithm for graph embedding with text information.
Sentence embedding models
A codebase for training and using models of sentence embeddings.
N-gram embedder
A tool for training and using character n-gram based word and sentence embeddings in natural language processing.
Materials Embeddings
Unsupervised word embeddings capture latent knowledge from materials science literature
ynqa/wego476
Word embeddings library
An open-source Go library for learning and manipulating vector representations of words
N-gram embeddings
A repository providing a re-implementation of character n-gram embeddings for pre-training in natural language processing tasks
