arXiv Machine Learning July 20, 2026 By Joshua Ho, Benjamin Ryan Roberts, Shuo Han, Haichen Wang

Pretrained Event Classification Model for High Energy Physics Analysis

Read the original on arXiv Machine Learning →

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 collision events spanning 12 distinct physics processes.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging

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