Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
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Updated
Jul 25, 2024 - Jupyter Notebook
Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
all kinds of baseline models for long text classificaiton( text categorization)
This is the implementation for the paper: Sequential Recommender System based on Hierarchical Attention Network
Repository of state of the art text/documentation classification algorithms in Pytorch.
Paper code for Pruning and Sparsemax Methods for Hierarchical Attention Networks
Text-level Aspect-Based Sentiment Analysis based on multi-task approach for Vietnamese reviews.
Notebooks for running and visualizing results using trained models for linguistic complexity.
Text Classification Lib on Keras
THANOS is a modification in HAN (Hierarchical Attention Network) architecture. Here we use Tree LSTM to obtain the embeddings for each sentence.
I implemented 3HAN(Hierarchical Attention Network)for fake news detection in pytorch. The same model can be modified and trained for different text classification tasks.
Tensorflow implementation of attention mechanism for text classification tasks.
Implementation of a Hierarchical Attention Network (HAN) in PyTorch
Project files for pattern recognition group assignment (team 22) @ Utrecht University.
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