WhatliesToolkit to help understand "what lies" in word embeddings. Also benchmarking!
Catalyst🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
Cw2veccw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information
DeepehrChronic Disease Prediction Using Medical Notes
KprnReasoning Over Knowledge Graph Paths for Recommendation
Magnetloss PytorchPyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.
CauseCode for the Recsys 2018 paper entitled Causal Embeddings for Recommandation.
SensegramMaking sense embedding out of word embeddings using graph-based word sense induction
VectoraiVector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.
Research2vecRepresenting research papers as vectors / latent representations.
ParallaxTool for interactive embeddings visualization
Vec4irWord Embeddings for Information Retrieval
Datastories Semeval2017 Task4Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".
JodieA PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"
Cx db8a contextual, biasable, word-or-sentence-or-paragraph extractive summarizer powered by the latest in text embeddings (Bert, Universal Sentence Encoder, Flair)
CofactorCoFactor: Regularizing Matrix Factorization with Item Co-occurrence
Entity2recentity2rec generates item recommendation using property-specific knowledge graph embeddings
Pytorch NlpBasic Utilities for PyTorch Natural Language Processing (NLP)
Embedding As ServiceOne-Stop Solution to encode sentence to fixed length vectors from various embedding techniques
ElastiknnElasticsearch plugin for nearest neighbor search. Store vectors and run similarity search using exact and approximate algorithms.
Keras Vgg16 Places365Keras code and weights files for the VGG16-places365 and VGG16-hybrid1365 CNNs for scene classification
Graph2gaussGaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".
Chars2vecCharacter-based word embeddings model based on RNN for handling real world texts
Hash EmbeddingsPyTorch implementation of Hash Embeddings (NIPS 2017). Submission to the NIPS Implementation Challenge.
Dna2vecdna2vec: Consistent vector representations of variable-length k-mers
SytoraA sophisticated smart symptom search engine
Diff2vecReference implementation of Diffusion2Vec (Complenet 2018) built on Gensim and NetworkX.
MagnitudeA fast, efficient universal vector embedding utility package.
Scikit Fusionscikit-fusion: Data fusion via collective latent factor models
Hdc.caffeComplete Code for "Hard-Aware-Deeply-Cascaded-Embedding"
VerseReference implementation of the paper VERSE: Versatile Graph Embeddings from Similarity Measures
Dict2vecDict2vec is a framework to learn word embeddings using lexical dictionaries.
CesiWWW 2018: CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information
Stock RnnPredict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
DutchembeddingsRepository for the word embeddings experiments described in "Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource", presented at LREC 2016.
Graph 2d cnnCode and data for the paper 'Classifying Graphs as Images with Convolutional Neural Networks' (new title: 'Graph Classification with 2D Convolutional Neural Networks')
Entity embeddings categoricalDiscover relevant information about categorical data with entity embeddings using Neural Networks (powered by Keras)
Deeplearning Nlp ModelsA small, interpretable codebase containing the re-implementation of a few "deep" NLP models in PyTorch. Colab notebooks to run with GPUs. Models: word2vec, CNNs, transformer, gpt.
FinalfrontierContext-sensitive word embeddings with subwords. In Rust.
Ml Surveys📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Pytorch Continuous Bag Of WordsThe Continuous Bag-of-Words model (CBOW) is frequently used in NLP deep learning. It's a model that tries to predict words given the context of a few words before and a few words after the target word.
EmbeddingsvizVisualize word embeddings of a vocabulary in TensorBoard, including the neighbors
Philo2vecAn implementation of word2vec applied to [stanford philosophy encyclopedia](http://plato.stanford.edu/)
DogembeddingsRare pupper image compression model for word-embedding-esque operations.
Keras Textclassification中文长文本分类、短句子分类、多标签分类、两句子相似度(Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN
BpembPre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)
Deep MihashCode for papers "Hashing with Mutual Information" (TPAMI 2019) and "Hashing with Binary Matrix Pursuit" (ECCV 2018)
RoleoWeb based semantic visualization tool
Eda nlpData augmentation for NLP, presented at EMNLP 2019
NatashaSolves basic Russian NLP tasks, API for lower level Natasha projects