Nettsider med emneord «Machine Learning»
The project "Pandemics, Particles and Parameter (s)paces" is a cross-disciplinary collaboration between theoretical physics at the University of Oslo and the Norwegian Institute of Public Health (NIPH/FHI) aimed at developing software to meet the United Nations Sustainable Development Goal 3, in particular Target 3.d: "Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks."
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The PLUMBIN' project is a cross-disciplinary collaboration between high-energy physics and statistics aimed at making powerful computational tools for exploring the fundamental constituents of the Universe.
Thesis presented in 2020
Model independent searches for new physics are proposed as a way to be sensitive to various scenarios of new physics theories in final states with e.g. leptons recorded with the ATLAS detector.
Thesis presented in 2019
Insights is a 4-year Marie Sklodowska-Curie Innovative Training Networks project for the career development of 12 Early Stage Researchers (ESRs) at 10 partner institutions across Europe. INSIGHTS is focused on applying the latest advances in statistics, and in particular machine learning, to particle physics.
