Destructive Deep Learning (ddl) documentation

• Destructive Deep Learning (ddl) README
  • Documentation
  • Environment Setup
  • Installation
  • Reproduce experiments from ICML 2018 paper
• Contributing
  • General coding guidelines
  • Project-specific guidelies
• MNIST Demo
  • Load and preprocess MNIST
  • Train deep copula model
  • Comparing MNIST samples to other methods
  • Exploring the discovered MNIST latent space
• Quickstart Tutorial
  • Destructors
  • Composite destructors (Implicit density)
  • Deep destructors
  • Working with destructors in an unbounded domain (Deep Gaussian copula destructors)
• ICML 2018 Toy Experiment
• API Reference
  • ddl.autoregressive
  • ddl.base
  • ddl.datasets
  • ddl.deep
  • ddl.externals
  • ddl.externals.mlpack
  • ddl.gaussian
  • ddl.independent
  • ddl.linear
  • ddl.local
  • ddl.mixture
  • ddl.tree
  • ddl.univariate
  • ddl.utils
  • ddl.validation
• Changelog
  • [Unreleased]
  • [0.0.2] - 2018-08-21
  • [0.0.1] - 2018-06-11