A list of recent papers regarding deep learning and deep reinforcement learning. They are sorted by time to see the recent papers first. I will renew the recent papers and add notes to these papers.

You should find the papers and software with star flag are more important or popular.

Table of Contents

• Papers

• Model Zoo

• Pretrained Model

• Courses

• Books

• Software

• Applications

• Awesome Projects

Papers

• 2017 year

• deep learning

• deep reinforcement learning

• natural language process

• 2016 year

• deep learning

• deep reinforcement learning

• natural language process

• 2015 year

• 2014 year

• 2013 year

• 2012 year

• 2011 year

• 2010 year

• before 2010 year

Model Zoo

• 2012 | AlexNet | pdf | https://github.com/kratzert/finetune_alexnet_with_tensorflow |

• 2013 | RCNN | arxiv | https://github.com/rbgirshick/rcnn |

• 2014 | CGNA | arxiv | https://github.com/zhangqianhui/Conditional-Gans |

• 2014 | DeepFaceVariant | pdf | https://github.com/joyhuang9473/deepid-implementation |

• 2014 | GAN | arxiv | https://github.com/goodfeli/adversarial |

• 2014 | GoogLeNet | pdf | https://github.com/google/inception |

• 2014 | OverFeat | arxiv | https://github.com/sermanet/OverFeat |

• 2014 | SPPNet | arxiv | https://github.com/yhenon/keras-spp |

• 2014 | VAE | arxiv | https://github.com/dpkingma/nips14-ssl |

• 2014 | VGGNet | arxiv | https://gist.github.com/ksimonyan/211839e770f7b538e2d8 |

• 2015 | DCGAN | arxiv | https://github.com/carpedm20/DCGAN-tensorflow |

• 2015 | DRAW | arxiv | https://github.com/ericjang/draw |

• 2015 | Global And Local Attention | arxiv | https://github.com/giancds/tsf_nmt |

• 2015 | FaceNet | arxiv | https://github.com/davidsandberg/facenet |

• 2015 | Fast RCNN | arxiv | https://github.com/rbgirshick/fast-rcnn |

• 2015 | Faster RCNN | arxiv | https://github.com/rbgirshick/py-faster-rcnn |

• 2015 | FCNT | pdf | https://github.com/scott89/FCNT |

• 2015 | Inception | arxiv | https://github.com/tensorflow/models/tree/master/inception |

• 2015 | LAPGAN | arxiv | https://github.com/facebook/eyescream |

• 2015 | NeuralGPU | arxiv | https://github.com/tensorflow/models/tree/master/neural_gpu |

• 2015 | Pointer Net | arxiv | https://github.com/devsisters/pointer-network-tensorflow |

• 2015 | ResNet | arxiv1 , arxiv2, arxiv3 | https://github.com/tensorflow/models/tree/master/resnet |

• 2015 | Skip-Thought Vectors | pdf | https://github.com/tensorflow/models/tree/master/skip_thoughts |

• 2015 | Transformer | arxiv | https://github.com/tensorflow/models/tree/master/transformer |

• 2016 | Dp_sgd | arxiv | https://github.com/tensorflow/models/tree/master/differential_privacy |

• 2016 | EnergyGAN | arxiv | https://github.com/buriburisuri/ebgan |

• 2016 | Grad-CAM | arxiv | https://github.com/Ankush96/grad-cam.tensorflow |

• 2016 | Im2txt | arxiv | https://github.com/tensorflow/models/tree/master/im2txt |

• 2016 | InfoGAN | arxiv | https://github.com/buriburisuri/supervised_infogan |

• 2016 | Multiple_teachers | arxiv | https://github.com/tensorflow/models/tree/master/differential_privacy |

• 2016 | Neural Programmer | pdf | https://github.com/tensorflow/models/tree/master/neural_programmer |

• 2016 | PCNN | arxiv | https://github.com/kundan2510/pixelCNN |

• 2016 | Pix2Pix | arxiv | https://github.com/yenchenlin/pix2pix-tensorflow |

• 2016 | PVANet | arxiv | https://github.com/sanghoon/pva-faster-rcnn |

• 2016 | R-FCN | arxiv | https://github.com/Orpine/py-R-FCN |

• 2016 | SeqGAN | pdf | https://github.com/LantaoYu/SeqGAN |

• 2016 | SqueezeNet | arxiv | https://github.com/songhan/SqueezeNet-Deep-Compression |

• 2016 | Swivel | arxiv | https://github.com/tensorflow/models/tree/master/swivel |

• 2016 | SyntaxNet | arxiv | https://github.com/tensorflow/models/tree/master/syntaxnet |

• 2016 | Textsum | | https://github.com/tensorflow/models/tree/master/textsum |

• 2016 | VGNA | arxiv | https://github.com/Shuangfei/vgan |

• 2017 | Learning to Remember Rare Events | pdf | https://github.com/tensorflow/models/tree/master/learning_to_remember_rare_events |

• 2017 | SalGAN | arxiv | https://github.com/imatge-upc/saliency-salgan-2017 |

• 2017 | WGAN | arxiv | https://github.com/Zardinality/WGAN-tensorflow |

Pretrained Model

• Available pretrained word embeddings

• Inception-v3 of imagenet

• Dependency-Based Word Embeddings.

• GloVe: Global Vectors for Word Representation

• Model of the deep residual network used for cifar10

• Pre-Trained Doc2Vec Models

• Pre-trained word vectors 

  ⭐️

• ResNet in TensorFlow Pretrain Model

• TensorFlow VGG-16 pre-trained model

• VGGNets for Scene Recognition

Courses

• [Utah] Applied Computational Genomics Course at UU

• [Stanford] CS231n: Convolutional Neural Networks for Visual Recognition

• [CUHK] ELEG 5040: Advanced Topics in Signal Processing(Introduction to Deep Learning)

• [Stanford] CS224n: Natural Language Processing with Deep Learning

• [Oxford] Deep Learning by Prof. Nando de Freitas

• [NYU] Deep Learning by Prof. Yann LeCun

• [Berkeley] CS294: Deep Reinforcement Learning

• [Berkeley] Stat212b：Topics Course on Deep Learning

• [MIT] S094: Deep Learning for Self-Driving Cars

• [CUHK] ELEG 5040: Advanced Topics in Signal Processing (Introduction to Deep Learning)

• [Stanford] CS20SI: Tensorflow for Deep Learning Research

• [Stanford] CS224n: Natural Language Processing with Deep Learning

• [MIT] S191: Introduction to Deep Learning

• [吴立德] 《深度学习课程》

• [Oxford] Deep Learning Course

• [David Silver] RL Course

• [MIT] Practical Deep Learning For Coders

• [Google] Udacity Deep Learning Online Course

Books

• Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, [zh]

• Neural Networks and Deep Learning by Michael Nielsen

• Deep Learning Tutorial by LISA lab, University of Montreal

• 神经网络与深度学习.邱锡鹏

• UFLDL Tutorial

• Rules of Machine Learning: Best Practices for ML Engineering

• Reinforcement Learning: An Introduction [code]

• Reinforcement LearningState-of-the-Art

• A Course in Machine Learning

• 深度学习入门 by PaddlePaddle

• TensorFlow For Machine Intelligence

• First Contact With TensorFlow

• Learning scikit-learn: Machine Learning in Python

Software

• python

• [Pylearn2] Theano-based deep learning libraries

• [Blocks] Blocks is a framework that helps you build neural network models on top of Theano 

  ⭐️

• [Lasagne] Lightweight library to build and train neural networks in Theano.

• [Chainer] Chainer bridge the gap between algorithms and implementations of deep learning.

• [ChainerRL] ChainerRL is a deep reinforcement learning library built on top of Chainer.

• [DeepPy] DeepPy is a Pythonic deep learning framework built on top of NumPy.

• [Deepnet] Deepnet: a GPU-based python implementation of deep learning algorithms.

• [Deepgaze] Deepgaze: A computer vision library for human-computer interaction based on CNNs

• [DeepQA] Tensorflow implementation of "A neural conversational model", a Deep learning based chatbot.

• [DeepVideoAnalytics] Analyze videos & images, perform detections, index frames & detected objects, search by examples.

• [Edward] Edward: A library for probabilistic modeling, inference, and criticism.

• [Elephas] Distributed Deep learning with Keras & Spark.

• [Gensim] Gensim: Deep learning toolkit implemented in python programming language intended for handling large text collections, using efficient algorithms.

• [Hebel] Hebel: A library for deep learning with neural networks in Python using GPU acceleration with CUDA through PyCUDA.

• [Keras] Keras: Deep Learning library for Theano and TensorFlow. 

  ⭐️

• [Kur] Kur: Descriptive Deep Learning. 

  ⭐️

• [Neon] Neon is Nervana's Python based Deep Learning framework.

• [PyTorch] Tensors and Dynamic neural networks in Python with strong GPU acceleration. 

  ⭐️

• [Scikit-Learn] scikit-learn: machine learning in Python. 

  ⭐️

• [Skll] SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

• [TensorFX] TensorFX is an end to end application framework to simplifies machine learning with TensorFlow

• [Theano] Theano: Mathematical library in Python, maintained by LISA lab

• C++

• [MinPy] MinPy: Providing a high performing and flexible deep learning platform, by prototyping a pure NumPy interface above MXNet backend.

• [Caffe] Caffe: Deep learning framework by the BVLC 

  ⭐️

• [CNTK] CNTK:The Microsoft Cognitive Toolkit.

• [DeepDetect] DeepDetect : Open Source Deep Learning Server & API

• [DIGITS] NVIDIA DIGITS is a new system for developing, training and visualizing deep neural networks.

• [DSSTNE] DSSTNE is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models.

• [PaddlePaddle] PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use, efficient, flexible and scalable deep learning platform.

• [MXNet] MXNet: A flexible and efficient deep learning library for heterogeneous distributed systems with multi-language support 

  ⭐️

• [Singa] Singa: Singa is an Apache Incubating project for developing an open source deep learning library.

• [Tensorflow] Tensorflow: An open source software library for numerical computation using data flow graph by Google 

  ⭐️

• [Tiny-dnn] Tiny-dnn is a C++11 implementation of deep learning.

• Java

• [CoreNLP] Stanford CoreNLP: A Java suite of core NLP tools.

• [Deeplearning4J] Deeplearning4J: Neural Net Platform.

• [Librec] LibRec: A Java Library for Recommender Systems.

• [NeuralNetworks] This is a Java implementation of some of the algorithms for training deep neural networks.

• [NewralNet] A lightweight, easy to use and open source Java library for experimenting with feed-forward neural nets and deep learning.

• Scala

• [BigDL] BigDL: Distributed Deep learning on Apache Spark.

• Julia

• [Knet] Knet: Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia.

• [Mocha] Mocha is a Deep Learning framework for Julia, inspired by the C++ framework Caffe.

• Js

• [Keras-js] Run Keras models (tensorflow backend) in the browser, with GPU support.

• [Neurojs] A javascript deep learning and reinforcement learning library.

• Matlab

• [MatConvNet] MatConvNet: CNNs for MATLAB

• Lua

• [OpenNMT] OpenNMT: Open-Source Neural Machine Translation

• [Torch7] Torch7: Deep learning library in Lua, used by Facebook and Google Deepmind 

  ⭐️

• Php

• [PHP-ML] PHP-ML - Machine Learning library for PHP

Applications

• pytorch

• A fast and differentiable QP solver for PyTorch.

• A PyTorch Implementation of Single Shot MultiBox Detector.

• A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing

• Comprehensive Data Augmentation and Sampling for Pytorch

• CNNs for Sentence Classification in PyTorch

• Deep Q-Learning Network in pytorch

• Fast Neural Style for Image Style Transform by Pytorch

• Highway networks implemented in PyTorch.

• OpenNMT: Open-Source Neural Machine Translation in PyTorch 

  ⭐️

• PyTorch implementation of Fully Convolutional Networks

• PyTorch implementation of Global Vectors for Word Representation

• PyTorch implementation of the Value Iteration Networks

• Pytorch Negative Sampling Loss

• Pytorch Poetry Generation

• Sequence to Sequence Models with PyTorch

• SSD: Single Shot MultiBox Object Detector, in PyTorch

• t-SNE experiments in pytorch

• YOLOv2 in PyTorch

• theano

• CNN-yelp-challenge-2016-sentiment-classification

• Deep Neural Network for Sentiment Analysis on Twitter

• Implementations of many popular deep learning models in Theano+Lasagne

• tensorflow

• A framework for developing and evaluating reinforcement learning algorithms

• A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.

• An implementation of Pix2Pix in Tensorflow for use with frames from films

• A Practical Guide for Debugging TensorFlow Codes

• A set of Deep Reinforcement Learning Agents implemented in Tensorflow. 

  ⭐️

• Aspect Based Sentiment Analysis using End-to-End Memory Networks

• A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks" 

  ⭐️

• A TensorFlow implementation of Baidu's DeepSpeech architecture

• DeepColor: Automatic coloring and shading of manga-style lineart

• Deep Learning based Python Library for Stock Market Prediction and Modelling

• Deepnlp:Deep Learning NLP Pipeline implemented on Tensorflow

• Embedding Watermarks into Deep Neural Networks

• Fast Multi(Interpolative) Style Transfer

• Fast PixelCNN++: speedy image generation

• Fully differentiable deep-neural decision forest in tensorflow

• GA3C: Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU

• Implementation of Generative Adversarial Networks, for Audio.

• Interactive, node-by-node debugging and visualization for TensorFlow 

  ⭐️

• Machine Learning on Sequential Data Using a Recurrent Weighted Average

• Metasploit for machine learning.

• Multilabel time series classification with LSTM

• Neural Relation Extraction implemented with LSTM in TensorFlow

• PixelVAE with or without regularization

• PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 

  ⭐️

• Realistic Handwriting with Tensorflow

• Real-time Joint Semantic Reasoning for Autonomous Driving

• Self-Driving Car Engineer Nanodegree

• Sequence-to-Sequence Grapheme-to-Phoneme toolkit

• Simple Recommender System using Denoising AutoEncoder, implemented using TensorFlow

• SSD in TensorFlow: Traffic Sign Detection and Classification

• Tensorflow implementation of fast neural style transfer

• TensorFlow on iOS demo

• TensorFlowOnSpark

• Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets 

  ⭐️

• Tensorflow Tutorial files and Implementations of various Deep NLP and CV Models

• Tutorials for deep learning

• 使用TensorFlow实现的Sequence to Sequence的聊天机器人模型

• Udacity SDC: Vehicle Detection 

  ⭐️

• Keras

• Embedding Watermarks into Deep Neural Networks

• Experimental implementation of novel neural network structures

• keras-emoji-embeddings

• Wasserstein DCGAN in Tensorflow/Keras

Awesome Projects

• 15 AI and Machine Learning Events

• Awesome Adversarial Machine Learning

• Awesome-Caffe

• Awesome Deep Learning

• Awesome Deep learning papers and other resources

• Awesome Deep Vision

• Awesome - Most Cited Deep Learning Papers

• Awesome Public Datasets

• Awesome PyTorch 

  ⭐️

• Awesome Reinforcement Learning

• Awesome Robotics

• Awesome Sentiment Analysis

• Awesome TensorFlow 

  ⭐️

• Chainer Info

• Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch 

  ⭐️

• Collection of reinforcement learners implemented in python.

• Datasets, Transforms and Models specific to Computer Vision

• Deep Learning Papers Reading Roadmap

• Machine Learning Videos

• Machine Learning From Scratch

• Paper list of multi-agent reinforcement learning (MARL)

• SCODE Word Embeddings using Substitute Words

• Summaries and notes on Deep Learning research papers

• The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch 

  ⭐️

• Various math-related things in Python code

• 用于对话系统的中英文语料

链接：

https://github.com/endymecy/awesome-deeplearning-resources

原文链接：

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