PyTorch implementation of normalizing flow models

Constrained optimization toolkit for PyTorch

Official PyTorch implementation of "HiNet: Deep Image Hiding by Invertible Network" (ICCV 2021)

Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.

[NeurIPS 2022] (Amortized) distributional control for pre-trained generative models

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

A python/pytorch package for invertible neural networks

MintNet: Building Invertible Neural Networks with Masked Convolutions

Multi-fidelity Generative Deep Learning Turbulent Flows

Learning inverse kinematics using invertible neural networks and GANs. Research project for "Advanced Deep Learning for Robotics".

Code for Transformed Distribution Matching (TDM) for Missing Value Imputation, ICML 2023

Results of my master thesis. Conditional invertible neural networks in the freia framework were used to dertermine the CO2 concentration using spectra taken by the satellite OCO2.

This contains my pytorch implementation of Glow from OpenAI.

FrEIA sample code

Invertible Rescaling Networks

Code for the paper "Guided Image Generation with Conditional Invertible Neural Networks" (2019)