Python implementation of bag-of-concepts

The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).

SCAN: Learning to Classify Images without Labels (ECCV 2020), incl. SimCLR.

Word Embeddings (e.g. Word2Vec) in Go!

Multiple implementations for abstractive text summurization , using google colab

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

Fast vectorization, topic modeling, distances and GloVe word embeddings in R.

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

Dict2vec is a framework to learn word embeddings using lexical dictionaries.

An implementation of "Network Representation Learning with Rich Text Information" (IJCAI '15).

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

Learning to Cluster. A deep clustering strategy.

(NeurIPS 2020 oral) Code for "Deep Transformation-Invariant Clustering" paper

Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP

Assessing Source Code Semantic Similarity with Unsupervised Learning

Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.

Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

TCyb 2018: Graph learning for multiview clustering

Machine Learning (EE 5184) in NTU