446 Open source projects that are alternatives of or similar to rnn-theano

Load forcasting on Delhi area electric power load using ARIMA, RNN, LSTM and GRU models

This is my graduation project in BIT. Title: Noise Reduction Using GRU.

Deep Learning

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

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

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.

[RSE21] Pytorch code for hierarchical time series classification with multi-stage convolutional RNN

A toolkit for neural language modeling using Tensorflow including basic models like RNNs and LSTMs as well as more advanced models.

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Jupyter notebooks for Chainer hands-on

THEANO-KALDI-RNNs is a project implementing various Recurrent Neural Networks (RNNs) for RNN-HMM speech recognition. The Theano Code is coupled with the Kaldi decoder.

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.

Haste: a fast, simple, and open RNN library

Keras tutorial for beginners (using TF backend)

RNN and general weights, gradients, & activations visualization in Keras & TensorFlow

Porting of Skip-Thoughts pretrained models from Theano to PyTorch & Torch7

Part-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

[PAMI 2021] Gating Revisited: Deep Multi-layer RNNs That Can Be Trained

Word Embedding + LSTM + FC

Boilerplate code for quickly getting set up to run language modeling experiments

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano

language model in Chinese，基于Pytorch官方文档实现

Recurrent Additive Networks for Tensorflow

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

RNN(SimpleRNN, LSTM, GRU) Tensorflow2.0 & Keras Notebooks (Workshop materials)

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

light deep neural network tools box(LSTM,GRU,RNN,CNN,Bi-LSTM,etc)

[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

In PyTorch Learing Neural Networks Likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

Neural Machine Translation with Keras

机器学习、深度学习、NLP实战项目

Predict Cryptocurrency Price with Deep Learning

百度云魅族深度学习应用大赛

🔬 Nano size Theano LSTM module

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow

📓 Notes for Andrew Ng's courses on deep learning

The project uses state of the art deep learning on collected data for automatic analysis of emotions.

language models toolkits with hierarchical softmax setting

Implementation of Hierarchical Attention Networks in PyTorch

A Keras library for multi-step time-series forecasting.

Project 4 for Metis bootcamp. Objective was generation of character-level RNN trained on Donald Trump's statements using Keras. Also generated Markov chains, and quick pyTorch RNN as baseline. Attempted semi-supervised GAN, but was unable to test in time.

An experimental web text editor that runs a LSTM model while you write to suggest new lines

Official code of our work, Unified Pre-training for Program Understanding and Generation [NAACL 2021].

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

Keras and PyTorch implementations of the MaLSTM model for computing Semantic Similarity.

An RNN (GRU) TensorFlow Android App for word prediction.

🧠👨‍💻Deep Learning Specialization • Lecture Notes • Lab Assignments

LSTM, GRU cell implementation from scratch in tensorflow

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

Official repo of the article: Yousef, W. A., Ibrahime, O. M., Madbouly, T. M., & Mahmoud, M. A. (2019), "Learning meters of arabic and english poems with recurrent neural networks: a step forward for language understanding and synthesis", arXiv preprint arXiv:1905.05700

CIKM AnalytiCup 2017 is an open competition that is sponsored by Shenzhen Meteorological Bureau, Alibaba Group and CIKM2017. Our team got the third place in the first phrase. And in the second phrase we got the fourth place.

Relation Classification - SEMEVAL 2010 task 8 dataset

bitcoin prediction algorithms

Application of machine learning to the Coinbase (GDAX) orderbook

My implementation of "Hierarchical Attention Networks for Document Classification" in Keras

Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction