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Top 233 recurrent-neural-networks open source projects

Relational Rnn Pytorch
An implementation of DeepMind's Relational Recurrent Neural Networks in PyTorch.
Echotorch
A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.
Variational Recurrent Autoencoder Tensorflow
A tensorflow implementation of "Generating Sentences from a Continuous Space"
Cs224d
Code for Stanford CS224D: deep learning for natural language understanding
Rnn ctc
Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
Im2latex Tensorflow
Tensorflow implementation of the HarvardNLP paper - What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)
Attention Mechanisms
Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.
Iseebetter
iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
Protein Sequence Embedding Iclr2019
Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019
Coursera Deep Learning Specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Pytorch Kaldi
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
Deep News Summarization
News summarization using sequence to sequence model with attention in TensorFlow.
Mss pytorch
Singing Voice Separation via Recurrent Inference and Skip-Filtering Connections - PyTorch Implementation. Demo:
Sru
SRU is a recurrent unit that can run over 10 times faster than cuDNN LSTM, without loss of accuracy tested on many tasks.
Emotion Recognition Using Speech
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Keras Lmu
Keras implementation of Legendre Memory Units
Lrp for lstm
Layer-wise Relevance Propagation (LRP) for LSTMs
Tfvos
Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.
Stock Price Predictor
This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
Speech Recognition Neural Network
This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.
Arc Pytorch
The first public PyTorch implementation of Attentive Recurrent Comparators
Document Classifier Lstm
A bidirectional LSTM with attention for multiclass/multilabel text classification.
Stockprediction
Plain Stock Close-Price Prediction via Graves LSTM RNNs
Deep Lyrics
Lyrics Generator aka Character-level Language Modeling with Multi-layer LSTM Recurrent Neural Network
Rcnn Text Classification
Tensorflow Implementation of "Recurrent Convolutional Neural Network for Text Classification" (AAAI 2015)
Rnn From Scratch
Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs
Linear Attention Recurrent Neural Network
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)
Skiprnn 2017 Telecombcn
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks (ICLR 2018)
Rnn Text Classification Tf
Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification
Chemgan Challenge
Code for the paper: Benhenda, M. 2017. ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.
Handwriting Synthesis
Handwriting Synthesis with RNNs ✏️
Easyesn
Python library for Reservoir Computing using Echo State Networks
Multitask sentiment analysis
Multitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587
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