University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Bayesian methods in cosmology

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Bayesian methods in cosmology

Download to your calendar using vCal

If you have a question about this talk, please contact nobody.

RNTW01 - Rich and Nonlinear Tomography (RNT) in Radar, Astronomy and Geophysics

Bayesian inference methods are widely used to analyse observations in cosmology, but they can be extremely computationally demanding. Recent work in this area has focussed on developing new methods for greatly accelerating such analyses, in particular by using nested sampling and machine learning methods. I will give a brief outline of these approaches, which are generic in nature, and illustrate their use in a cosmological case study.

This talk is part of the Isaac Newton Institute Seminar Series series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

An audience with Nic Benns, Film and TV Sequence Director Business and Society Research Group Marine/Wolfson Building lecture hall.

Other talks

Title to be confirmed Cambridge AI in Medicine Seminar - July 2026 Am I a Member? Auditing Private Machine Learning The LMC-SMC System: A New Laboratory for Galaxy Evolution, Dynamics and Dark Matter Cooperation for Nature The role of radiation in cancer care: a spotlight on cancers of the oesophagus, head and neck
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity