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https://github.com/stefanwebb/flowtorch-old
Separating Normalizing Flows code from Pyro and improving API
https://github.com/stefanwebb/flowtorch-old
bayesian-inference bayesian-statistics normalizing-flows probabilistic-graphical-models probabilistic-models probabilistic-programming pytorch
Last synced: 4 months ago
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Separating Normalizing Flows code from Pyro and improving API
- Host: GitHub
- URL: https://github.com/stefanwebb/flowtorch-old
- Owner: stefanwebb
- License: mit
- Created: 2020-12-07T22:37:50.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2021-08-26T05:37:58.000Z (almost 3 years ago)
- Last Synced: 2024-01-16T10:45:56.977Z (5 months ago)
- Topics: bayesian-inference, bayesian-statistics, normalizing-flows, probabilistic-graphical-models, probabilistic-models, probabilistic-programming, pytorch
- Language: Python
- Homepage: https://flowtorch.ai
- Size: 4.2 MB
- Stars: 36
- Watchers: 6
- Forks: 1
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
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- awesome-stars - stefanwebb/flowtorch-old - Separating Normalizing Flows code from Pyro and improving API (Python)
README
[](https://github.com/stefanwebb/flowtorch/actions?query=workflow%3A%22Python+package%22)
Copyright (c) FlowTorch Development Team.
This source code is licensed under the MIT license found in the
[LICENSE.txt](https://github.com/stefanwebb/flowtorch/blob/master/LICENSE.txt) file in the root directory of this source tree.
> :boom: **This repository contains an archived version of Flowtorch from early 2021. Development has continued in a private repo.**.
# Overview
FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called [Normalizing Flows](https://arxiv.org/abs/1908.09257).
# Installing
An easy way to get started is to install from source:
git clone https://github.com/stefanwebb/flowtorch.git
cd flowtorch
pip install -e .
# Further Information
We refer you to the [FlowTorch website](https://flowtorch.ai) for more information about installation, using the library, and becoming a contributor. Here is a handy guide:
* [What are normalizing flows?](https://flowtorch.ai/users)
* [How do I install FlowTorch?](https://flowtorch.ai/users/installation)
* [How do I construct and train a distribution?](https://flowtorch.ai/users/start)
* [How do I contribute new normalizing flow methods?](https://flowtorch.ai/dev)
* [Where can I report bugs?](https://github.com/stefanwebb/flowtorch/issues)
* [Where can I ask general questions and make feature requests?](https://github.com/stefanwebb/flowtorch/discussions)
* [What features are planned for the near future?](https://github.com/stefanwebb/flowtorch/projects)