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Showing 1 to 4 of 4 for “"MultiNest"”.

  1. Bayesian methods for gravitational waves and neural networks

    … is combined with the nested sampling algorithm MULTINEST to provide rapid Bayesian inference. Using samples from the normal inference, a network is trained on the likelihood function and eventually used in its place. This is able to provide significant increase in the speed of Bayesian inference …

    cambridge Repository record for Bayesian methods for gravitational waves and neural networks (opens in a new tab)

  2. Investigating the AMI SZ Selection Function of Galaxy Clusters

    … approach are modelled and then analysed with MULTINEST. PROFILE was then used to create simulated AMI observations with varying noise realizations (thermal, cosmic microwave background (CMB) and source confusion) and then analysed with McAdam. A pipeline was developed to allow the application …

    cambridge Repository record for Investigating the AMI SZ Selection Function of Galaxy Clusters (opens in a new tab)

  3. Bayesian Methods and Machine Learning in Astrophysics

    This thesis is concerned with methods for Bayesian inference and their applications in astrophysics. We principally discuss two related themes: advances in nested sampling (Chapters 3 to 5), and Bayesian sparse reconstruction of signals from noisy data (Chapters 6 and 7). Nested sampling is a …

    cambridge Repository record for Bayesian Methods and Machine Learning in Astrophysics (opens in a new tab)

  4. Computational Bayesian techniques applied to cosmology

    This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well constrained. They present interesting challenges for Bayesian inference, which attempts to quantify our knowledge of the universe …

    cambridge Repository record for Computational Bayesian techniques applied to cosmology (opens in a new tab)