Naresh1318/Adversarial_Autoencoder
TensorFlow implementation of adversarial autoencoders for generative modeling and classification.
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This repository provides an educational implementation of adversarial autoencoders, a deep learning technique that combines autoencoders with adversarial training. It includes code for training autoencoders, exploring latent space, disentangling style and content, and performing semi-supervised classification using only 1000 labeled MNIST samples. The project comes with Medium blog posts explaining each concept.
Frequently asked
- What is Naresh1318/Adversarial_Autoencoder?
- TensorFlow implementation of adversarial autoencoders for generative modeling and classification.
- Is Adversarial_Autoencoder open source?
- Yes — Naresh1318/Adversarial_Autoencoder is open source, released under the MIT license.
- What language is Adversarial_Autoencoder written in?
- Naresh1318/Adversarial_Autoencoder is primarily written in Python.
- How popular is Adversarial_Autoencoder?
- Naresh1318/Adversarial_Autoencoder has 434 stars on GitHub.
- Where can I find Adversarial_Autoencoder?
- Naresh1318/Adversarial_Autoencoder is on GitHub at https://github.com/Naresh1318/Adversarial_Autoencoder.