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Introducing Gedi, a Python package for Gaussian process regression

João D. R. Camacho

A challenge in science appears in how to perform the analysis of different types of data, and from it successfully determine relationships that further expand our knowledge of the environment around us. In astronomy one tool available are Gaussian processes, a powerful non-parametric Bayesian tool for modeling real-world statistical problems in a non-parametric model.
In this cookie, I will present a Python package, developed for my Master thesis, that uses Gaussian processes in the analysis of radial velocity data. I will show what type of results we are able to obtain with this new tool and in what future work we will be able to apply it.

2017 April 26, 13:30

Centro de Astrofísica da Universidade do Porto (Classroom)
Rua das Estrelas, 4150-762 Porto

Faculdade de Ciências da Universidade de Lisboa Universidade do Porto Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Fundação para a Ciência e a Tecnologia COMPETE 2020 PORTUGAL 2020 União Europeia