pingcsu/FrEIA

Framework for Easily Invertible Architectures

This is the Framework for Easily Invertible Architectures (FrEIA).

• Construct Invertible Neural Networks (INNs) from simple invertible building blocks.
• Quickly construct complex invertible computation graphs and INN topologies.
• Forward and inverse computation guaranteed to work automatically.
• Most common invertible transforms and operations are provided.
• Easily add your own invertible transforms.

Table of contents

• Papers
• Installation
  • Through pip
  • Manually
  • Documentation

Papers

Our following papers use FrEIA, with links to code given below.

"Generative Classifiers as a Basis for Trustworthy Image Classification" (CVPR 2021)

• Paper: https://arxiv.org/abs/2007.15036
• Code: https://github.com/RayDeeA/ibinn_imagenet

"Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (Neurips 2020)

• Paper: arxiv.org/abs/2001.06448
• Code: github.com/VLL-HD/exact_information_bottleneck

"Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (ICLR 2020)

• Paper: arxiv.org/abs/2001.04872
• Code: github.com/VLL-HD/GIN

"Guided Image Generation with Conditional Invertible Neural Networks" (2019)

• Paper: arxiv.org/abs/1907.02392
• Supplement: drive.google.com/file/d/1_OoiIGhLeVJGaZFeBt0OWOq8ZCtiI7li
• Code: github.com/VLL-HD/conditional_invertible_neural_networks

"Analyzing inverse problems with invertible neural networks." (ICLR 2019)

• Paper: arxiv.org/abs/1808.04730
• Code: github.com/VLL-HD/analyzing_inverse_problems

Installation

FrEIA has the following dependencies:

Package	Version
Python	>= 3.7
Pytorch	>= 1.0.0
Numpy	>= 1.15.0
Scipy	>= 1.5

Through pip

pip install git+https://github.com/VLL-HD/FrEIA.git

Manually

For development:

# first clone the repository
git clone https://github.com/VLL-HD/FrEIA.git
cd FrEIA
# install the dependencies
pip install -r requirements.txt
# install in development mode, so that changes don't require a reinstall
python setup.py develop

Documentation

The full manual can be found at https://vll-hd.github.io/FrEIA including

• Quickstart guide
• Tutorial
• Examples
• API documentation