831 Open source projects that are alternatives of or similar to Hierarchical-Word-Sense-Disambiguation-using-WordNet-Senses

Deep-learning models of NTUA-SLP team submitted in SemEval 2018 tasks 1, 2 and 3.

Attention-based multimodal fusion for sentiment analysis

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".

Sentiment Analysis: Deep Bi-LSTM+attention model

CRNN with attention to do OCR,add Chinese recognition

Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning

CNN, LSTM, NBOW, fasttext 中文文本分类

Machine learning, in numpy

Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.

KU_NERDY 이동엽, 임희석 (2017 국어 정보 처리 시스템경진대회 금상) - 한글 및 한국어 정보처리 학술대회

Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering | Python3 | PyTorch | CNNs | Causality | Reasoning | LSTMs | Transformers | Multi-Head Self Attention | Published in IEEE Winter Conference on Applications of Computer Vision (WACV) 2021

Various implementations and projects on CNN, RNN, LSTM, GAN, etc

Image captioning using attention models

基於關聯式新聞提取方法之雙階段注意力機制模型用於股票預測

Sorting numbers with pointer networks

My Attempt(s) In The World Of ML/DL....

中文聊天机器人，基于10万组对白训练而成，采用注意力机制，对一般问题都会生成一个有意义的答复。已上传模型，可直接运行，跑不起来直播吃键盘。

Implementation of papers for text classification task on DBpedia

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

Seq2Seq, Bert, Transformer, WaveNet for time series prediction.

nlp lecture-notes and source code

从模型训练到部署，实战知识图谱(Knowledge Graph)&自然语言处理(NLP)。涉及 Tensorflow, Bert+Bi-LSTM+CRF,Neo4j等 涵盖 Named Entity Recognition,Text Classify,Information Extraction,Relation Extraction 等任务。

An easy-to-use named entity recognition (NER) toolkit, implemented the Bi-LSTM+CRF model in tensorflow.

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

LSTM-CRF for NER with ConLL-2002 dataset

Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record

Playground for implementing custom layers and other components compatible with keras, with the purpose to learn the framework better and perhaps in future offer some utils for others.

This repo contains a PyTorch implementation of a BiLSTM-CRF model for named entity recognition task.

Code for ANA at SemEval-2019 Task 3

Voice activity detection (VAD) toolkit including DNN, bDNN, LSTM and ACAM based VAD. We also provide our directly recorded dataset.

Enhanced BiLSTM Inference Model for Natural Language Inference

📚 Text classification library with Keras

Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971

document classification using LSTM + self attention

Bangla Machine Translator

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

Language Modelling Makes Sense - WSD (and more) with Contextual Embeddings

datagrand 2019 information extraction competition rank9

Predict materials properties using only the composition information!

attention-based LSTM/Dense implemented by Keras

🎨 🎨NLP 自然语言处理教程 🎨🎨 https://dataxujing.github.io/NLP-paper/

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

No description or website provided.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Chinese Poetry Generation

Attention-based bidirectional LSTM for Classification Task (ICASSP)

Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

keras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS

基于 Bi-LSTM 和 CRF 的中文语义角色标注

Neat (Neural Attention) Vision, is a visualization tool for the attention mechanisms of deep-learning models for Natural Language Processing (NLP) tasks. (framework-agnostic)

Implementation of various self-attention mechanisms focused on computer vision. Ongoing repository.

A bidirectional LSTM with attention for multiclass/multilabel text classification.

Tensorflow-LSTM-CRF tool for Named Entity Recognizer

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

An implementation of the Show, Attend and Tell paper in Tensorflow, for the OpenAI Im2LaTeX suggested problem