Title: Farewell talk

Abstract: The last decade has seen vast progress in the field of probabilistic large-scale structure inference, which differs in intent from traditional measurements of statistical summaries from galaxy survey catalogues. Before leaving the ICG in a few months, I will review my contributions of the last two years to the field, highlighting two different approaches: likelihood-based and likelihood-free.

Building upon the application of the likelihood-based method BORG to Sloan Digital Sky Survey data, I will show detailed characterisations of dynamic cosmic web environments. In doing so, I will discuss a natural connection with information theory.

I will then present ongoing work about likelihood-free inference with generative cosmological models. The proposed approach reduces the number of required simulations by several orders of magnitude, yet the computational cost remains a major challenge. As an answer, in the last part, I will discuss an innovative approach for embarrassingly parallel cosmological simulations, based on a spatial splitting of the considered volume.