8 citations · 15 across the 4 of their papers we have counts for
4 papers
EveNet: A Foundation Model for Particle Collision Data Analysis
Ting-Hsiang Hsu, Bai-Hong Zhou, Qibin Liu +8
While deep learning is transforming data analysis in high-energy physics, computational challenges limit its potential. We address these challenges in the context of collider physi…
Entanglement and Bell Nonlocality in at the LHC using Machine Learning for Neutrino Reconstruction
Yulei Zhang, Bai-Hong Zhou, Qi-Bin Liu +5
Experiments at the CERN Large Hadron Collider (LHC) have accumulated an unprecedented amount of data corresponding to a large variety of quantum states. Although searching for new…
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka +66
We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge. We study state-of-the-art generative models on four calorimeter shower datasets of i…
Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation
Qibin Liu, Chase Shimmin, Xiulong Liu +3
We introduce a novel machine learning method developed for the fast simulation of calorimeter detector response, adapting vector-quantized variational autoencoder (VQ-VAE). Our mod…