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各类神经网络及文献整理(附下载链接)

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常见神经网络出处及下载链接

一、CNN及其变体
二、RNN及其变体
三、Transformer及其变体
四、生成对抗网络GAN及其变体
五、特殊网络
总览

整理下这些年主要的神经网络文献，包括了三大特征提取器（CNN/RNN/Transformer）、GAN等一些混合模型。不定期补充更新

一、CNN及其变体

序号	网络结构	文献出处	年份
1	LeNet-5(CNN起源)	Generalization and Network Design Strategies	1989
2	VGGNet	VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION	2014
3	Inception	Rethinking the Inception Architecture for Computer Vision	2016
4	ResNet	Deep Residual Learning for Image Recognition	2016
5	DenseNet	Densely Connected Convolutional Networks	2017

二、RNN及其变体

序号	网络结构	文献出处	年份
1	RNN(起源)	Learning representations by back-propagating errors	1986
2	LSTM	Long short-term memory	1997
3	BiLSTM	Framewise phoneme classification with bidirectional LSTM and other neural network architectures	2005
4	GRU	Learning Phrase Representations Using RNN Encoder–Decoder for Statistical Machine Translation	2014

三、Transformer及其变体

序号	网络结构	文献出处	年份
1	Transformer(起源)	Attention is all you need	2017
2	Vision Transformer (ViT)	An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	2020
3	Pooling-based Vision Transformer (PiT)	Rethinking spatial dimensions of vision transformers	2021

四、生成对抗网络GAN及其变体

序号	网络结构	文献出处	年份
1	GAN(起源)	Generative Adversarial Networks	2014
2	CGAN	Conditional Generative Adversarial Nets	2014
3	InfoGAN	Infogan: Interpretable representation learning by information maximizing generative adversarial nets	2016

五、特殊网络

这里包括了混合模型以及特殊的图卷积网络GCN，虽然GCN借鉴了CNN的思想，但是从结构上和计算方式上，差异还是挺大的。所以单独在这里列出。

序号	网络结构	文献出处	年份
1	CLDNN	Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks	2015
2	GCN(图卷积)	Semi-supervised Classification with Graph Convolutional Networks	2016

总览

序号	网络结构	文献出处	年份
1	RNN(序列模型起源)	Learning representations by back-propagating errors	1986
2	CNN(卷积网络起源)	Generalization and Network Design Strategies	1989
3	LSTM	Long short-term memory	1997
4	BiLSTM	Framewise phoneme classification with bidirectional LSTM and other neural network architectures	2005
5	VGGNet	VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION	2014
6	GRU	Learning Phrase Representations Using RNN Encoder–Decoder for Statistical Machine Translation	2014
7	GAN	Generative Adversarial Networks	2014
8	CGAN	Conditional Generative Adversarial Nets	2014
9	CLDNN	Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks	2015
10	Inception	Rethinking the Inception Architecture for Computer Vision	2016
11	ResNet	Deep Residual Learning for Image Recognition	2016
12	GCN(图卷积)	Semi-supervised Classification with Graph Convolutional Networks	2016
13	InfoGAN	Infogan: Interpretable representation learning by information maximizing generative adversarial nets	2016
14	DenseNet	Densely Connected Convolutional Networks	2017
15	Transformer(起源)	Attention is all you need	2017
16	Vision Transformer (ViT)	An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	2020
17	Pooling-based Vision Transformer (PiT)	Rethinking spatial dimensions of vision transformers	2021