Outputs (2)

Constraints on primordial gravitational waves from the cosmic microwave background (2020)
Journal Article
Clarke, T. J., Copeland, E. J., & Moss, A. (2020). Constraints on primordial gravitational waves from the cosmic microwave background. Journal of Cosmology and Astroparticle Physics, 2020(10), Article 002. https://doi.org/10.1088/1475-7516/2020/10/002

Searches for primordial gravitational waves have resulted in constraints in a large frequency range from a variety of sources. The standard Cosmic Microwave Background (CMB) technique is to parameterise the tensor power spectrum in terms of the tenso... Read More about Constraints on primordial gravitational waves from the cosmic microwave background.

Accelerated Bayesian inference using deep learning (2020)
Journal Article
Moss, A. (2020). Accelerated Bayesian inference using deep learning. Monthly Notices of the Royal Astronomical Society, 496(1), 328-338. https://doi.org/10.1093/mnras/staa1469

We present a novel Bayesian inference tool that uses a neural network (NN) to parametrize efficient Markov Chain Monte Carlo (MCMC) proposals. The target distribution is first transformed into a diagonal, unit variance Gaussian by a series of non-lin... Read More about Accelerated Bayesian inference using deep learning.