压缩内有pdf和epub两种格式的书籍。前言如下：PyTorch is grabbing the attention of data science professionals and deep learning practitioners due to its flexibility and ease of use. This book introduces the fundamental building blocks of deep learning and PyTorch. It de
This file contains:Deep Learning and Missing Data in Engineering Systems (2019, Springer International Publishing).pdf Deep Learning Classifiers with Memristive Networks_ Theory and Applications (2020, Springer International Publishing).pdf Deep Lea
深度学习模型不确定性领域重要文献，主要介绍了贝叶斯方法和SGLD优化算法，以及重要性采样算法，包括Yarin Gal的博士论文，Marco Tulio Ribeiro的“Why Should I Trust You?”和Alex Kendall的What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?等经典论文
基于 An Introduction to deep learning for physical layer 论文进行的one hot vector的autoencoder的matlab仿真实现。
文件包含：
m文件
autoencoder_one_hot 主程序包含网络的定义，训练及测试
NormalizationLayer 归一化层
gaussianNoiseLayer 噪声层
BLER_test 测试网络的BLER
constellation_test 测试网络生成信
