SimpleMC

Cosmological parameter estimation code developed by Dr. A. Slosar and Dr. JA Vazquez. From 2019 to 2023, I helped in maintaining the code, and incorporating nested sampling, convergence criteria for Metropolis-Hastings, post-processing options and other new features.

Collaborating with Dr. JA Vazquez.

Links:

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nnogada

Neural Networks Optimized by Genetic Algorithms in Data Analysis (nnogada).

Links:

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neuralike

Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up.

Links:

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crann

CRANN (Cosmological Reconstructions with Artificial Neural Networks). Python notebooks with model-independent reconstructions for cosmological functions. We will soon clean up the code and shape it into a library for ease of use.

Links:

  • Cosmological Reconstructions with Artificial Neural Networks (arXiv).
  • Repository in GitHub.

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