Deep Learning（深度学习）学习笔记（不断更新）：
相关Paper（不断更新）
笔者先从多个渠道整理了几篇，后续边看边更新。
1、Densely Connected Convolutional Networks
2、Learning From Simulated and Unsupervised Images through Adversarial Training
3、Annotating Object Instance with a Polygon-RNN
4、YOLO9000: Better, Faster, Stronger
5、Computational Imaging on the Electric Grid
6、Object retrieval with large vocabularies and fast spatial matching
7、Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning
8、Pointing the Unknown Words
9、LightRNN Memory and Computation-Efficient Recurrent Neural Network
10、Language Modeling with Gated Convolutional Networks
11、Recurrent neural network based language model
12、Extensions of Recurrent Neural Network Language Model
13、A guide to recurrent neural networks and backpropagation
14、Training Recurrent Neural Networks
15、Recurrent Neural Networks for Language Understanding
16、Empirical Evaluation and Combination of Advanced Language Modeling Techniques
17、Speech Recognition with Deep Recurrent Neural Networks
18、A fast learning algorithm for deep belief nets
19、Large Scale Distributed Deep Networks
20、Context Dependent Pretrained Deep Neural Networks fo Large Vocabulary Speech Recognition
21、An Empirical Study of Learning Rates in Deep Neural Networks for Speech Recognition
22、Deep Neural Networks for Acoustic Modeling in Speech Recognition
23、Deep Belief Networks Using Discriminative Features for Phone Recognition
24、Improving Deep Neural Networks For LVCSR using Rectified Linear Units and Dropout
25、Improved feature processing for Deep Neural Networks
26、Exploiting Sparseness in Deep Neural Networks fo Large Vocabulary Speech Recognition
27、Learning Features from Music Audio with Deep Belief Networks
28、Making Deep Belief Networks Effective for Large Vocabulary Continuous Speech Recognition
29、Robust Visual Recognition Using Multilayer Generative Neural Networks
30、Deep Convolutional Network Cascade for Facial Point Detection
31、ImageNet Classification with Deep Convolutional Neural Networks
32、Gradient-Based Learning Applied to Document Recognition
33、Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
34、Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis
35、Multi-GPU Training of ConvNets
36、Deep Learning For Signal And Information Processing
37、Deep Convex Net: A Scalable Architecture for Speech Pattern Classification
38、Improving Wideband Speech Recognition using Mixed-Bandwidth Training Data in CD-DNN-HMM
39、On Rectified Linear Units for Speech Processing
更新中。。。
相关书籍（不断更新）
笔者刚着手学习，非大牛，不敢说“推荐”书籍，仅罗列所看的。
1、Deep Learning，出自Goodfellow、Bengio 和 Courville 三位大牛之手，笔者刚开始看，后续再对书籍作评论
如果需要《Deep Learning》中文电子版书籍，请后台回复“深度学习”获取
更新中。。。
更多精彩内容，欢迎扫码关注以下微信公众号：大数据技术宅。大数据、AI从关注开始
