Metadata-Version: 2.1
Name: sbijax
Version: 0.1.0
Summary:  Simulation-based inference in JAX
Project-URL: homepage, https://github.com/dirmeier/sbijax
Author-email: Simon Dirmeier <sfyrbnd@pm.me>
License-Expression: Apache-2.0
License-File: LICENSE
Keywords: abc,approximate Bayesian computation,normalizing flows,simulation-based inference,smc-abc
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.8
Requires-Dist: blackjax-nightly>=0.9.6.post127
Requires-Dist: distrax>=0.1.2
Requires-Dist: dm-haiku>=0.0.9
Requires-Dist: optax>=0.1.3
Requires-Dist: surjectors>=0.2.2
Requires-Dist: tfp-nightly>=0.20.0.dev20230404
Description-Content-Type: text/markdown

# sbijax

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[![ci](https://github.com/dirmeier/sbijax/actions/workflows/ci.yaml/badge.svg)](https://github.com/dirmeier/sbijax/actions/workflows/ci.yaml)
[![version](https://img.shields.io/pypi/v/sbijax.svg?colorB=black&style=flat)](https://pypi.org/project/sbijax/)

> Simulation-based inference in JAX

## About

SbiJAX implements several algorithms for simulation-based inference using
[JAX](https://github.com/google/jax), [Haiku](https://github.com/deepmind/dm-haiku) and [BlackJAX](https://github.com/blackjax-devs/blackjax).

SbiJAX so far implements

- Rejection ABC (`RejectionABC`),
- Sequential Monte Carlo ABC (`SMCABC`),
- Sequential Neural Likelihood Estimation (`SNL`)
- Surjective Sequential Neural Likelihood Estimation (`SSNL`)
- Sequential Neural Posterior Estimation C (short `SNP`)

## Examples

You can find several self-contained examples on how to use the algorithms in `examples`.

## Usage

## Installation

Make sure to have a working `JAX` installation. Depending whether you want to use CPU/GPU/TPU,
please follow [these instructions](https://github.com/google/jax#installation).

To install from PyPI, just call the following on the command line:

```bash
pip install sbijax
```

To install the latest GitHub <RELEASE>, use:

```bash
pip install git+https://github.com/dirmeier/sbijax@<RELEASE>
```

## Author

Simon Dirmeier <a href="mailto:sfyrbnd @ pm me">sfyrbnd @ pm me</a>
