N. Srimanobhas

collaborators

2 papers

hep-ph2026

Weight-Based Representation Learning for Parameter Inference in Monte Carlo Simulations

Vichayanun Wachirapusitanand, Norraphat Srimanobhas

We present a Machine Learning-based approach for parameter inference in physics models that exploits event-level weights provided by simulators. Individual observations may have we…

hep-ph2026

Searching for Lepton Flavor Violating decays of the Higgs Boson into $I^¼ I ¨ $ , $e I ¨ $ , and $e I^¼$ final states at FCC-ee

P. Sriling, N. Srimanobhas, P. Uttayarat +2

We investigate the projected sensitivity of the FCC-ee in probing the LFV decay of the 125 GeV Higgs boson, $h \to I^¼ I ¨ $ , $h \to e I ¨ $ , and $h \to e I^¼$ at center-of-mass energy of 240…

Weight-Based Representation Learning for Parameter Inference in Monte Carlo Simulations

Searching for Lepton Flavor Violating decays of the Higgs Boson into I^¼I¨, eI¨, and eI^¼ final states at FCC-ee

Searching for Lepton Flavor Violating decays of the Higgs Boson into $I^¼ I ¨ $ , $e I ¨ $ , and $e I^¼$ final states at FCC-ee