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Showing 1 to 3 of 3 for “"likelihood-free inference"”.

  1. Gradient-based dimension reduction for Bayesian inverse problems and simulation-based inference

    Inference is a pervasive task in science and engineering applications. The Bayesian approach to inference facilitates informed decision making by quantifying uncertainty in parameters and predictions, but can be computationally demanding. This thesis focuses on Bayesian methods for inverse problems …

    mit Repository record for Gradient-based dimension reduction for Bayesian inverse problems and simulation-based inference (opens in a new tab)

  2. Geographic Migration and Evolution of Streptococcus pneumoniae

    … approach using Bayesian optimization for Likelihood-free inference. Incorporating thousands of pneumococcal genomes from South Africa, Malawi, The Gambia, and Kenya I included only neutral sites. I estimated migration rates and directions of migration between countries. I found some …

    cambridge Repository record for Geographic Migration and Evolution of Streptococcus pneumoniae (opens in a new tab)

  3. Simulation-based Bayesian machine learning methods for Cosmology and beyond

    … sampler is motivated by the limitations of likelihood-based Bayesian inference in sky-averaged 21-cm Cosmology. Moreover, PolySwyft merges nested sampling and neural ratio estimation into a general Bayesian framework, and the method is a general-purpose algorithm applicable beyond Cosmology. …

    cambridge Repository record for Simulation-based Bayesian machine learning methods for Cosmology and beyond (opens in a new tab)