PyAutoencoder

A library providing ready-to-use implementations of state-of-the-art autoencoder architectures in PyTorch.

Contents:

• Getting Started
  • Installation
  • Quick Start
  • Core Concepts
• Architecture & Design
  • Overview
  • Vanilla Autoencoder (AE)
  • Variational Autoencoder (VAE)
  • Adaptive Group Variational Autoencoder (AdaGVAE)
  • Loss Functions
  • Key Design Principles
• API Reference
  • Base Classes & Utilities
  • Autoencoder Models
  • Loss Functions & Utilities
  • Stochastic Layers
• Examples
  • MNIST Vanilla Autoencoder Example
  • Reproducing Kingma & Welling (2013), Fig. 2 (MNIST VAE)