https://www.zhihu.com/topic/20084849/hot
resnet（残差网络）的F（x）究竟长什么样子？
https://www.zhihu.com/question/53224378
如何理解微软的深度残差学习？
https://www.zhihu.com/question/38499534?sort=created
SKIP CONNECTIONS ELIMINATE SINGULARITIES
https://arxiv.org/pdf/1701.09175.pdf
详解残差网络
https://zhuanlan.zhihu.com/p/42706477
残差网络原理
https://blog.csdn.net/qq_30478885/article/details/78828734
https://www.coursera.org/lecture/convolutional-neural-networks/why-resnets-work-XAKNO
https://arxiv.org/pdf/1512.03385.pdf
https://www.quora.com/How-does-deep-residual-learning-work
https://arxiv.org/pdf/1603.05027.pdf
Resnet中残差块的作用是完成恒等变换，那这样的恒等变换的意义是什么，在网络中能起到怎样的作用呢？
https://www.zhihu.com/question/293243905
https://zhuanlan.zhihu.com/p/28124810
https://arxiv.org/pdf/1502.03167v3.pdf
https://zhuanlan.zhihu.com/p/31645196
https://www.coursera.org/lecture/convolutional-neural-networks/why-resnets-work-XAKNO
https://arxiv.org/pdf/1506.01497v3.pdf
https://arxiv.org/pdf/1504.08083.pdf
https://arxiv.org/pdf/1311.2524v5.pdf
https://arxiv.org/pdf/1702.08591.pdf
https://arxiv.org/pdf/1611.05431.pdf
https://arxiv.org/pdf/1607.07032.pdf
https://arxiv.org/abs/1605.06431
Residual Networks 理解
协方差
https://www.zhihu.com/question/20852004
ResNet架构可逆！多大等提出性能优越的可逆残差网络
一文简述ResNet及其多种变体
TensorFlow 实现 Resnet V2 代码解读
Identity Mapping in ResNet
1. 学习吴恩达在coursera的“深度学习课程”中关于源码地址在此。
【1】He K, Zhang X, Ren S, et al. Deep residual learning for image recognition[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 770-778.
【2】Srivastava R K, Greff K, Schmidhuber J. Highway networks[J]. arXiv preprint arXiv:1505.00387, 2015.
【3】Orhan A E, Pitkow X. Skip connections eliminate singularities[J]. arXiv preprint arXiv:1701.09175, 2017.
【4】Shang W, Sohn K, Almeida D, et al. Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units[J]. 2016:2217-2225.
【5】Greff K, Srivastava R K, Schmidhuber J. Highway and Residual Networks learn Unrolled Iterative Estimation[J]. 2017.
【6】Jastrzebski S, Arpit D, Ballas N, et al. Residual connections encourage iterative inference[J]. arXiv preprint arXiv:1710.04773, 2017.