cosmulator: accelerating cosmological inference with JAX machine-learning emulators on GPU
- Author:
Dily Duan Yi Ong
- License:
MIT
- Homepage:
cosmulator trains JAX normalising-flow emulators of nested-sampling posteriors on GPU, so a distribution can be resampled instantly for fast marginalisation and Bayesian evidence, and manages the resulting emulators (training, validation, storage and serving) across a grid of cosmological models and surveys.
Developed under a UKRI-funded high performance computing (DiRAC) project.
Installation
pip install cosmulator # inspect and use emulators (numpy only)
pip install "cosmulator[train]" # adds the JAX training stackRequires Python 3.11 or later.
1 maintainer
Metadata
1 maintainer
Release files for cosmulator 0.0.35
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| File | Size | Uploaded | Provenance | Actions |
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