7 citations · 16 across the 3 of their papers we have counts for
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hep-ex2026
Reinforcement Learning in High-Energy Physics: A Survey from Accelerator Control to Theory Exploration
Luca Anzalone
Reinforcement learning (RL) is a machine learning paradigm in which an agent learns a decision-making policy by interacting with an environment, guided by a scalar reward rather th…
hep-ex2023★ 4 cited
Triggering Dark Showers with Conditional Dual Auto-Encoders
Luca Anzalone, Simranjit Singh Chhibra, Benedikt Maier +2
We present a family of conditional dual auto-encoders (CoDAEs) for generic and model-independent new physics searches at colliders. New physics signals, which arise from new types…
hep-ex2022★ 5 cited
Improving Parametric Neural Networks for High-Energy Physics (and Beyond)
Luca Anzalone, Tommaso Diotalevi, Daniele Bonacorsi
Signal-background classification is a central problem in High-Energy Physics (HEP), that plays a major role for the discovery of new fundamental particles. A recent method -- the P…