cosmologyinformed
Cosmology-informed refers to approaches that deliberately integrate cosmological knowledge, theory, and physical constraints into data analysis, modeling, and interpretation. It emphasizes aligning methods with established cosmological physics rather than relying solely on data-driven patterns.
In practice, cosmology-informed methods employ forward models based on cosmological theories, use informative priors grounded in
Common applications include Bayesian parameter estimation in cosmology, where priors reflect measurements of the Hubble parameter,
Benefits of cosmology-informed methods include improved robustness with limited or noisy data, better generalization by enforcing