
How to unfold with AI
Inspired by high-dimensional data and the ideals of open science, high-energy physicists are using artificial intelligence to reimagine the statistical technique of ‘unfolding’.
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Inspired by high-dimensional data and the ideals of open science, high-energy physicists are using artificial intelligence to reimagine the statistical technique of ‘unfolding’.
Hackathons can kick-start your career, says hacker and entrepreneur Jiannan Zhang.
The 96th ICFA meeting heard extensive reports from the leading HEP laboratories and various world regions on their recent activities and plans.
Achieving a theoretical uncertainty of only a few per cent in the measurement of physical observables is a vastly challenging task in the complex environment of hadronic collisions.
Data on strokes is plentiful but fragmented, making it difficult to exploit in data-driven treatment strategies.
Findable, Accessible, Interoperable and Reusable: the sixth symposium of the European Open Science Cloud (EOSC) attracted over 1,000 participants.
Experts in data analysis, statistics and machine learning for physics came together from 9 to 12 September for PHYSTAT’s Statistics meets Machine Learning workshop.
By parking events triggered by a single muon, CMS collected an inclusive sample of approximately 10 billion b-hadrons in 2018.
As the harvest of data from the LHC experiments continues to increase, so does the required number of simulated collisions.
A new five-year-long project aims to accelerate novel computing, engineering and scientific ideas for the ATLAS and CMS upgrades.