normflows is a PyTorch implementation of discrete normalizing flows. Many popular flow architectures are implemented. The package can be easily installed via pip. The basic usage is described here, and a full documentation is available as well. A more detailed description of this package is given in out accompanying paper.
Implemented Flows
| Architecture | Reference |
|---|---|
| Planar Flow | Rezende & Mohamed, 2015 |
| Radial Flow | Rezende & Mohamed, 2015 |
| NICE | Dinh et al., 2014 |
| Real NVP | Dinh et al., 2017 |
| Glow | Kingma et al., 2018 |
| Masked Autoregressive Flow | Papamakarios et al., 2017 |
| Neural Spline Flow | Durkan et al., 2019 |
| Circular Neural Spline Flow | Rezende et al., 2020 |
| Residual Flow | Chen et al., 2019 |
| Stochastic Normalizing Flow | Wu et al., 2020 |
| licence_type: | The MIT License |
| Authors: | Vincent Stimper, Lukas Ryll, Timothy Gebhard, David Liu |
| Repository: | https://github.com/VincentStimper/normalizing-flows |
| Documentation: | https://vincentstimper.github.io/normalizing-flows/ |