https://github.com/maximevandegar/neb

Code for reproducing the experiments in the paper Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference.
https://github.com/maximevandegar/neb

empirical-bayes inverse-problems neural-empirical-bayes simulation-based-inference source-distribution-estimation

Last synced: about 2 months ago
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Code for reproducing the experiments in the paper Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference.

• Host: GitHub
• URL: https://github.com/maximevandegar/neb
• Owner: MaximeVandegar
• License: mit
• Created: 2020-12-09T10:29:21.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2022-06-21T02:29:10.000Z (over 2 years ago)
• Last Synced: 2023-03-04T19:58:47.681Z (almost 2 years ago)
• Topics: empirical-bayes, inverse-problems, neural-empirical-bayes, simulation-based-inference, source-distribution-estimation
• Language: Python
• Homepage:
• Size: 12 MB
• Stars: 8
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
![alt text](.imgs/header.jpg)

## Getting Started

```commandline

$ pip install -r requirements.txt

```

The implementation provides a simple interface that allows inference in a single line of code.

```python

from inference.neb import McBiasedEstimator, McUnbiasedEstimator, ElboEstimator, IwEstimator

# Define your data, likelihood function, source model, ...

estimator = McBiasedEstimator() 

estimator.infer(observations, source_model, optimizer, log_likelihood_fct)

```

The source code for the different estimators was written to be self-contained in a single file for a quick and easy understanding.

[Getting Started](https://github.com/MaximeVandegar/NEB/tree/main/examples)

## Cite

If you make use of this code in your work, please cite our paper:

```

@misc{vandegar2020neural,

      title={Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference}, 

      author={Maxime Vandegar and Michael Kagan and Antoine Wehenkel and Gilles Louppe},

      year={2020},

}

```