• Corpus ID: 244130365

Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation

@article{Cole2021FastAC,
  title={Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation},
  author={Alex Cole and Benjamin Kurt Miller and Samuel J. Witte and Maxwell Xu Cai and M. W. Grootes and Francesco Nattino and C Weniger},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.08030}
}
Sampling-based inference techniques are central to modern cosmological data analysis; these methods, however, scale poorly with dimensionality and typically require approximate or intractable likelihoods. In this paper we describe how Truncated Marginal Neural Ratio Estimation (tmnre) (a new approach in so-called simulation-based inference) naturally evades these issues, improving the (i) efficiency, (ii) scalability, and (iii) trustworthiness of the inference. Using measurements of the Cosmic… 

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