Deep learning driven jazz generation using Keras & Theano!
Har Stacked Residual Bidir Lstms
Using 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.
Pytorch implementation of CRNN (CNN + RNN + CTCLoss) for all language OCR.
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Efficient, transparent deep learning in hundreds of lines of code.
A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
Reasoning Over Knowledge Graph Paths for Recommendation
Haste: a fast, simple, and open RNN library
Deep learning for Arabic text Vocalization - التشكيل الالي للنصوص العربية
Doc Han Att
Hierarchical Attention Networks for Chinese Sentiment Classification
Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
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
Char Rnn Chinese
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch. Based on code of https://github.com/karpathy/char-rnn. Support Chinese and other things.
A cute multi-layer LSTM that can perform like a human 🎶
Rnn For Joint Nlu
Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
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.
A visualization tool for understanding and debugging RNNs
Load forcasting on Delhi area electric power load using ARIMA, RNN, LSTM and GRU models
Fast and simple music and audio analysis using RNN in Python 🕵️♀️ 🥁
Hierarchical Attentive Recurrent Tracking
Recurrent neural network for audio noise reduction
Pytorch Image Comp Rnn
PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks
Variational Auto-Encoders in a Sequential Setting.
Query-Reduction Networks (QRN)
Our implementation of the paper "Embedding-based News Recommendation for Millions of Users"
Generate monophonic melodies with machine learning using a basic LSTM RNN
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)