nessai#
nessai (/ˈnɛsi/): Nested Sampling with Artificial Intelligence
nessai is a nested sampling algorithm for Bayesian Inference that incorporates normalising flows. It is designed for applications where the Bayesian likelihood is computationally expensive.
The code is available at: mj-will/nessai.
For questions or other support, please either use our gitter room or open an issue.
User guide
- Installation
- Running the sampler
- Understanding the outputs
- Standard sampler configuration
- Importance nested sampler
- Reparameterisations
- Normalising flows configuration
- Parallelisation with nessai
- Gravitational-wave inference
- Sampling with discrete parameters
- Plugins
- Further details
- FAQs
- API reference
Examples
Citing nessai#
If you find nessai useful in your work please cite the DOI for this code and our paper:
@software{nessai,
author = {Michael J. Williams},
title = {nessai: Nested Sampling with Artificial Intelligence},
month = feb,
year = 2021,
publisher = {Zenodo},
version = {latest},
doi = {10.5281/zenodo.4550693},
url = {https://doi.org/10.5281/zenodo.4550693}
}
@article{Williams:2021qyt,
author = "Williams, Michael J. and Veitch, John and Messenger, Chris",
title = "{Nested sampling with normalizing flows for gravitational-wave inference}",
eprint = "2102.11056",
archivePrefix = "arXiv",
primaryClass = "gr-qc",
doi = "10.1103/PhysRevD.103.103006",
journal = "Phys. Rev. D",
volume = "103",
number = "10",
pages = "103006",
year = "2021"
}
@article{Williams:2023ppp,
author = "Williams, Michael J. and Veitch, John and Messenger, Chris",
title = "{Importance nested sampling with normalising flows}",
eprint = "2302.08526",
archivePrefix = "arXiv",
primaryClass = "astro-ph.IM",
reportNumber = "LIGO-P2200283",
doi = "10.1088/2632-2153/acd5aa",
journal = "Mach. Learn. Sci. Tech.",
volume = "4",
number = "3",
pages = "035011",
year = "2023"
}