Dataset Open Access

Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains

Park, Ji Won; Wagner-Carena, Sebastian; Birrer, Simon; Marshall, Philip J.; Lin, Joshua Yao-Yu; Roodman, Aaron


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4300382", 
  "title": "Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains", 
  "issued": {
    "date-parts": [
      [
        2020, 
        12, 
        1
      ]
    ]
  }, 
  "abstract": "<p>We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, &quot;Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant.&quot; They are formatted to be used with the DESC package &quot;H0rton&quot; (<a href=\"https://github.com/jiwoncpark/h0rton\">https://github.com/jiwoncpark/h0rton</a>). Additional descriptions can be found in the README. Please contact Ji Won Park (@jiwoncpark) on GitHub or <a href=\"https://github.com/jiwoncpark/h0rton/issues\">make an issue</a> for any questions.</p>", 
  "author": [
    {
      "family": "Park, Ji Won"
    }, 
    {
      "family": "Wagner-Carena, Sebastian"
    }, 
    {
      "family": "Birrer, Simon"
    }, 
    {
      "family": "Marshall, Philip J."
    }, 
    {
      "family": "Lin, Joshua Yao-Yu"
    }, 
    {
      "family": "Roodman, Aaron"
    }
  ], 
  "version": "v1.0", 
  "type": "dataset", 
  "id": "4300382"
}
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