https://github.com/acids-ircam/pytorch_flows
Implementation and tutorials of normalizing flows with the novel distributions module
https://github.com/acids-ircam/pytorch_flows
Last synced: 5 months ago
JSON representation
Implementation and tutorials of normalizing flows with the novel distributions module
- Host: GitHub
- URL: https://github.com/acids-ircam/pytorch_flows
- Owner: acids-ircam
- License: gpl-3.0
- Created: 2019-02-06T16:22:47.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2020-08-13T15:45:51.000Z (over 5 years ago)
- Last Synced: 2025-06-23T17:15:34.990Z (6 months ago)
- Language: Jupyter Notebook
- Size: 5.49 MB
- Stars: 167
- Watchers: 8
- Forks: 18
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-energy-based-model - `pytorch_flows` - ircam](https://github.com/acids-ircam) (🧑💻 Code / <img src="assets/pytorch.svg" alt="PyTorch" height="20px"> PyTorch Repos)
- awesome-normalizing-flows - pytorch_flows - ircam](https://github.com/acids-ircam) (🧑💻 Repos <small>(18)</small> / <img src="assets/pytorch.svg" alt="PyTorch" height="20px"> PyTorch Repos)
README
# Normalizing flows with PyTorch
Implementation and tutorials of normalizing flows with the novel distributions module. The current set of tutorials and implementations is
1. [Implementing and optimizing planar flows](flows_01.ipynb)
2. [Different types of invertible flows (radial, batchnorm, affine)](flows_02.ipynb)
3. [Using flows in variational inference (VAEs)](flows_03.ipynb)
4. [Auto-regressive types of flows (RealNVP, MAF, IAF)](flows_04.ipynb)
**Still very much drafty work in progress**
5. More advanced and recent type of flows
Sorry everyone for the very long delay, we shall try to finish this tutorial session with new advances in generative flows (GLOW) and more advanced ideas (NODE, FFJORD) in the upcoming weeks :)