swyft 0.2.1

Nested ratio estimation and inhomogeneous poisson point process sample caching for simulator efficient marginal posterior estimation.

Check out the quickstart notebook -->

This is a beta release. If you encounter problems, please contact the authors or submit a bug report.

SWYFT

Truncated marginal neural ratio estimation

Installation

After installing pytorch, please run the command:

pip install swyft

Documentation

Detailed documentation can be found on readthedocs.

Instruction videos

• 1 - Linear regression with swyft
• 2 - ConvNets, parameter regression and swyft
• ...more to come...

Academic videos

• Truncated Marginal Neural Ratio Estimation

Related tools and repositories

• Our repository applying swyft to benchmarks and example inference problems is available at tmnre.
• sbi is a collection of likelihood-free / simulator-based methods

Citing

If you use swyft in scientific publications, please cite one or both:

Truncated Marginal Neural Ratio Estimation. Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger. https://arxiv.org/abs/2107.01214

Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time. Benjamin Kurt Miller, Alex Cole, Gilles Louppe, Christoph Weniger. https://arxiv.org/abs/2011.13951