819 Open source projects that are alternatives of or similar to sequence-rnn-py

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

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)

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

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.

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.

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

The Official Deep Learning Framework for Route-based Place Recognition

Deep learning driven jazz generation using Keras & Theano!

使用Theano实现的一些RNN代码，包括最基本的RNN，LSTM，以及部分Attention模型，如论文MLSTM等

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Lightweight C++11 library for building deep recurrent neural networks

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Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

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

Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs

A variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

Train LSTM to writer novel (HongLouMeng here) in Pytorch.

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

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

Python library for Reservoir Computing using Echo State Networks

News summarization using sequence to sequence model with attention in TensorFlow.

Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM

Code and pre-trained model for: Deep Semantic Role Labeling: What Works and What's Next

Implementation of a hierarchical CNN based model to detect Big Five personality traits

A bidirectional LSTM with attention for multiclass/multilabel text classification.

Plain Stock Close-Price Prediction via Graves LSTM RNNs

Keras implementation of Legendre Memory Units

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

Deep learning codes and projects using Python

Anomaly detection for temporal data using LSTMs

The RWTH extensible training framework for universal recurrent neural networks

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🔬 Nano size Theano LSTM module

Neural machine translator for English2German translation.

An implementation of RNN-RBM & GBRBM.

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

💻 Make machines learn so that you don't have to struggle to program them; The ultimate list

AIOpen是一个按人工智能三要素（数据、算法、算力）进行AI开源项目分类的汇集项目，项目致力于跟踪目前人工智能（AI）的深度学习（DL）开源项目，并尽可能地罗列目前的开源项目，同时加入了一些曾经研究过的代码。通过这些开源项目，使初次接触AI的人们对人工智能（深度学习）有更清晰和更全面的了解。

R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

Alternative approach for Adaptive Computation Time in TensorFlow

RNN-based generative models for speech.

RNN benchmarks of pytorch, tensorflow and theano

Probabilistic Dialogue Act Classification for the Switchboard Corpus using an LSTM model

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Using LSTM network for time series forecasting

Hands-on in-person workshop for Deep Learning with TensorFlow

This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.

LSTM based human activity recognition using smart phone sensor dataset

Recurrent Additive Networks for Tensorflow

RNN-LSTM that learns passwords from a starting list