232 Open source projects that are alternatives of or similar to Sru

Biologically-realistic recurrent convolutional neural networks

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks

Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks (ICLR 2018)

videos, lectures, blogs for Deep Learning

Deep-Plant: Plant Classification with CNN/RNN. It consists of CAFFE/Tensorflow implementation of our PR-17, TIP-18 (HGO-CNN & PlantStructNet) and MalayaKew dataset.

ECG classification programs based on ML/DL methods

Some of the ML and DL related reading materials, research papers that I've read

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

3D reconstruction with neural networks using Tensorflow. See link for Video (https://www.youtube.com/watch?v=iI6ZMST8Ri0)

Code for the paper: Benhenda, M. 2017. ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.

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

Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

Lyrics Generator aka Character-level Language Modeling with Multi-layer LSTM Recurrent Neural Network

Text Classification Algorithms: A Survey

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

SimpleDNN is a machine learning lightweight open-source library written in Kotlin designed to support relevant neural network architectures in natural language processing tasks

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)

Implementation of Simple Recurrent Unit in Keras

How to build RNNs and LSTMs from scratch with NumPy.

The source of the IJCAI2017 paper "Modeling Trajectory with Recurrent Neural Networks"

Top 200 deep learning Github repositories sorted by the number of stars.

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO

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

A Python package for gender classification.

PyTorch tutorial for learners

Python library for Reservoir Computing using Echo State Networks

Application of machine learning to the Coinbase (GDAX) orderbook

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

R interface to the keras library

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

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

Tensorflow Implementation of "Recurrent Convolutional Neural Network for Text Classification" (AAAI 2015)

Quantize weights and activations in Recurrent Neural Networks.

brain.js is a GPU accelerated library for Neural Networks written in JavaScript.

Neural machine translator for English2German translation.

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

A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.

The first public PyTorch implementation of Attentive Recurrent Comparators

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

A Neural Networking library based on NumPy only

Quasi-recurrent Neural Networks for Keras

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Deepmind Recurrent Environment Simulators paper implementation in tensorflow

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

Keras Temporal Convolutional Network.

Learning the Enigma with Recurrent Neural Networks

using rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc

The code for the MaD TwinNet. Demo page:

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

Layer-wise Relevance Propagation (LRP) for LSTMs

Who Let The Dogs Out? Modeling Dog Behavior From Visual Data https://arxiv.org/pdf/1803.10827.pdf

An Echo State Network module for PyTorch.

Tensorflow Implementation of Recurrent Convolutional Neural Network for Relation Extraction

Plain Stock Close-Price Prediction via Graves LSTM RNNs

Handwriting Synthesis with RNNs ✏️

Deep Learning based Automatic Speech Recognition with attention for the Nvidia Jetson.

Keras implementation of Legendre Memory Units

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.

深度学习与PyTorch入门实战视频教程 配套源代码和PPT

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