NIMA Neural Image Assessment (TIP 2018).pdf

Convolutional Neural Networks are very similar to ordinary Neural Networks from the previous chapter

神经网络的入门,定义,以及一些训练过程总结,常用的损失函数介绍,包括回归和分类,以及正则化,最后包括实例化实现

论文《Neural Collaborative Filtering》原文,其中有NAIS模型实验中使用的两个数据集详细描述

第1章绪论1．1目的1．2历史1．3应用1．4生物学的启示参考文献第2章神经元模型和网络结构2．1目的2．1　理论和实例2．2．1符号2．2．2　神经元模型2．2．3网络结构2．3小结2．4例题2．5

RecurrentNeuralNetworksforPredictionoffersanewinsightintothelearningalgorithms,architecturesandstabi

A Neural Conversational Model.pdf

Neural network training relies on our ability to find “good” minimizers of highly non-convex loss fu

Michael Nielsen http://neuralnetworksanddeeplearning.com/index.html Neural Networks and Deep Learnin

ABSTRACT.Thisarticleintroducesaspecialcollectionof20researcharticlesthatpresentcurrentdevelopmentsan

byLeoL.Pipino,YangW.Lee,andRichardY.Wang一篇不错的关于数据质量的论问题