Metadata-Version: 2.1
Name: sbi
Version: 0.8.0
Summary: Simulation-based inference.
Home-page: http://mackelab.org/sbi
Author: Álvaro Tejero-Cantero, Jakob H. Macke, Jan-Matthis Lückmann, Conor M. Durkan, Michael Deistler, Jan Bölts.
Author-email: sbi@mackelab.org
License: AGPLv3
Keywords: bayesian parameter inference system_identification simulator PyTorch
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Adaptive Technologies
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Games/Entertainment :: Simulation
Classifier: License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
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`sbi` is a PyTorch package for simulation-based inference. Simulation-based
inference is the process of finding the parameters of a simulator from observations.
`sbi` takes a Bayesian approach and returns a full posterior distribution over the
parameters, conditional on the observations.

`sbi` offers a simple interface for one-line posterior inference

```python
from sbi inference import infer
# import your simulator, define your prior on the parameters
parameter_posterior = infer(simulator, prior, method='SNPE')
```

`sbi` is a community project. It is the PyTorch successor of
[`delfi`](https://github.com/mackelab/delfi), and started life as a fork of Conor M. 
Durkan's `lfi`. Development is currently coordinated at the [mackelab](https://uni-tuebingen.de/en/research/core-research/cluster-of-excellence-machine-learning/research/research/cluster-research-groups/professorships/machine-learning-in-science/).

We would appreciate to hear how `sbi`is working for your simulation problems, and
welcome also bug reports, pull requests and any other feedback at
[github.com/mackelab/sbi](https://github.com/mackelab/sbi).


