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Physicists still manually classify high-energy collisions. A new model uses a graph neural network to classify events from 12 physics processes, trained on 120 million simulated collisions. This could speed up physics discoveries, but we don't know yet how well it generalizes to real data.
“arXiv:2412.10665v3 Announce Type: replace-cross Abstract: We introduce a foundation model for event classification in high-energy physics, built on a Graph Neural Network architecture and trained on 120 million simulated proton-proton colli…”
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ENTITY
Graph Neural Network, arXiv:2412.10665v3
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LAST OBSERVED
Aug 7, 2026