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hep-ph2025
Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties
Minxuan He, Claudius Krause, Daohan Wang
We present a dedicated graph neural network (GNN)-based methodology for the extraction of the Higgs boson signal strength , incorporating systematic uncertainties. The architect…
hep-ph2025
Unbinned inclusive cross-section measurements with machine-learned systematic uncertainties
Lisa Benato, Cristina Giordano, Claudius Krause +5
We introduce a novel methodology for addressing systematic uncertainties in unbinned inclusive cross-section measurements and related collider-based inference problems. Our approac…
hep-ph2025
BitHEP -- The Limits of Low-Precision ML in HEP
Claudius Krause, Daohan Wang, Ramon Winterhalder
The increasing complexity of modern neural network architectures demands fast and memory-efficient implementations to mitigate computational bottlenecks. In this work, we evaluate…