LAMPE is a simulation-based inference (SBI) package that focuses on amortized estimation of posterior distributions, without relying on explicit likelihood functions; hence the name Likelihood-free AMortized Posterior Estimation (LAMPE). The package provides PyTorch implementations of modern amortized simulation-based inference algorithms like neural ratio estimation (NRE), neural posterior estimation (NPE) and more. Similar to PyTorch, the philosophy of LAMPE is to avoid obfuscation and expose all components, from network architecture to optimizer, to the user such that they are free to modify or replace anything they like.
As part of the inference pipeline, lampe provides components to efficiently store and load data from disk, diagnose predictions and display results graphically.
Important
In an effort to unite communities, the development of LAMPE has stopped in favor of the sbi project. The sbi package already supports many of lampe's features, and you are welcome to submit issues and PRs for the features you would like to be ported to sbi.
The lampe package is available on PyPI, which means it is installable via pip.
pip install lampe
Alternatively, if you need the latest features, you can install it from the repository.
pip install git+https://github.com/probabilists/lampe
The documentation is made with Sphinx and Furo and is hosted at lampe.readthedocs.io.
If you have a question, an issue or would like to contribute, please read our contributing guidelines.