Parametric neural networks learn likelihood ratios to infer top-philic scalar resonances from dip patterns caused by signal-background interference in hadron collider data.
Falcon et al.,Pytorchlightning/pytorch-lightning: 0.7.6 release, May, 2020
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
hep-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Big Dipper, Help Me Find A Way -- Dip-hunting at hadron colliders
Parametric neural networks learn likelihood ratios to infer top-philic scalar resonances from dip patterns caused by signal-background interference in hadron collider data.