Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
Trained neural networks and requisite information and data for rnnoise-nu
RNN based Time-series Anomaly detector model implemented in Pytorch.
Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow
翻译 - 使用Tensorflow在Python中使用字符级语言模型的多层递归神经网络（LSTM，RNN）
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
The source of the IJCAI2017 paper "Modeling Trajectory with Recurrent Neural Networks"
Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.
rnn based model for recommendations
Chinese keyword spotting model using LSTM RNN
RNN, LSTM, GRU, Attention Model included.
PyTorch implementation of char-rnn (character-level language model)
lstm-rnn, seq2seq model and attention-seq2seq model for vessel trajectory prediction.
A (CNN+)RNN(LSTM/BiLSTM)+CRF model for sequence labelling.😏
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
The nanoGPT-style implementation of RWKV Language Model - an RNN with GPT-level LLM performance.
sliced-rnn
Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.
cnn+rnn: vgg(vgg16,vgg19)+rnn(LSTM, GRU), resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152)+rnnrnn(LSTM, GRU), inception_v4+rnn(LSTM, GRU), inception_resnet_v2+rnn(LSTM, GRU),.....
karpathy's char-rnn (https://github.com/karpathy/char-rnn) implementation by Chainer
Deep RNN, LSTM, GRU, GF-RNN, and GF-LSTMs in Julia
CRF-RNN Keras/Tensorflow version
Using Deep Learning for Emotion Classification on EEG signals (SEED Dataset). CNN, RNN, Hybrid model, and Ensemble
RNN Tutorial for Artists