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[ascl:2509.014] pySELFI: Python implmentation of the Simulator Expansion for Likelihood-Free Inference algorithm
The statistical software package pySELFI implements the Simulator Expansion for Likelihood-Free Inference (SELFI) algorithm. SELFI is part of the family of simulation-based inference (SBI) methods, which replace the use of the likelihood function with a data-generating "black-box" simulator. pySELFI supports different black-box simulators, optimizes prior hyperparameters for primordial power spectrum inference, and check for model misspecification using the Mahalanobis distance. The code also scores compression and calculation of Fisher-Rao distances.
Code site:
https://github.com/florent-leclercq/pyselfi https://florent-leclercq.eu/data.php?page=3
Described in:
https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.4237L
Bibcode:
2025ascl.soft09014L


ascl:2509.014
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