Paper Reading
Introduction
Dropout A Simple Way to Prevent Neural Networks from Overfitting
Adversarial Feature Learning
Adversarial Autoencoders
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Chapter 7 Regularization for Deep Learning
Generative Adversarial Nets
Auto-Encoding Variational Bayes
Intriguing properties of neural networks
OpenAI-Generative Models
Conditional Image Synthesis With Auxiliary Classifier GANs
Improved Techniques for Training GANs
Learning Transformations for Clustering and Classification
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Abstract
5 Empirical Validation of DCGANs Capabilities### 5.1 Classifying CIFAR-10 Using as A Feature Extractor
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