automatic-personality-prediction[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings
Stars: ✭ 43 (+79.17%)
Mutual labels: lstm, rnn, attention, attention-lstm
Pytorch Seq2seqTutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Stars: ✭ 3,418 (+14141.67%)
Mutual labels: lstm, rnn, attention
Time AttentionImplementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971
Stars: ✭ 52 (+116.67%)
Mutual labels: lstm, rnn, attention
Machine LearningMy Attempt(s) In The World Of ML/DL....
Stars: ✭ 78 (+225%)
Mutual labels: lstm, rnn, attention
Chinese Chatbot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。
Stars: ✭ 124 (+416.67%)
Mutual labels: lstm, rnn, attention
Rnn For Joint NluPytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)
Stars: ✭ 176 (+633.33%)
Mutual labels: lstm, rnn, attention
Crnn Audio ClassificationUrbanSound classification using Convolutional Recurrent Networks in PyTorch
Stars: ✭ 235 (+879.17%)
Mutual labels: lstm, rnn
Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
Stars: ✭ 3,209 (+13270.83%)
Mutual labels: lstm, rnn
Caption generatorA modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
Stars: ✭ 243 (+912.5%)
Mutual labels: lstm, rnn
Rnn ctcRecurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
Stars: ✭ 220 (+816.67%)
Mutual labels: lstm, rnn
tf-ran-cellRecurrent Additive Networks for Tensorflow
Stars: ✭ 16 (-33.33%)
Mutual labels: lstm, rnn
KprnReasoning Over Knowledge Graph Paths for Recommendation
Stars: ✭ 220 (+816.67%)
Mutual labels: lstm, rnn
NlstmNested LSTM Cell
Stars: ✭ 246 (+925%)
Mutual labels: lstm, rnn
LightnetEfficient, transparent deep learning in hundreds of lines of code.
Stars: ✭ 243 (+912.5%)
Mutual labels: lstm, rnn
Har Stacked Residual Bidir LstmsUsing deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.
Stars: ✭ 250 (+941.67%)
Mutual labels: lstm, rnn
keras-utility-layer-collectionCollection of custom layers and utility functions for Keras which are missing in the main framework.
Stars: ✭ 63 (+162.5%)
Mutual labels: rnn, attention
