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Published in 2024 at "Journal of High Energy Physics"
DOI: 10.1007/jhep06(2024)211
Abstract: Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome…
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Keywords:
system;
neural density;
density operators;
model open ... See more keywords
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Published in 2019 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/stz1960
Abstract: Likelihood-free inference provides a framework for performing rigorous Bayesian inference using only forward simulations, properly accounting for all physical and observational effects that can be successfully included in the simulations. The key challenge for likelihood-free…
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Keywords:
active learning;
likelihood free;
cosmology;
neural density ... See more keywords