| Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning YL Du, K Zhou, J Steinheimer, LG Pang, A Motornenko, HS Zong, ... The European Physical Journal C 80, 1-17, 2020 | 76 | 2020 |
| Deep learning jet modifications in heavy-ion collisions YL Du, D Pablos, K Tywoniuk Journal of High Energy Physics 2021 (3), 1-50, 2021 | 57 | 2021 |
| Critical behaviors near the (tri-) critical end point of QCD within the NJL model Y Lu, YL Du, ZF Cui, HS Zong The European Physical Journal C 75, 1-7, 2015 | 38 | 2015 |
| Discussions on the crossover property within the Nambu–Jona-Lasinio model Y Du, Z Cui, Y Xia, H Zong Physical Review D—Particles, Fields, Gravitation, and Cosmology 88 (11), 114019, 2013 | 36 | 2013 |
| Jet tomography in heavy-ion collisions with deep learning YL Du, D Pablos, K Tywoniuk Physical Review Letters 128 (1), 012301, 2022 | 35 | 2022 |
| Continuum study of the QCD phase diagram through an OPE-modified gluon propagator C Shi, YL Du, SS Xu, XJ Liu, HS Zong Physical Review D 93 (3), 036006, 2016 | 34 | 2016 |
| The two-flavor NJL model with two-cutoff proper time regularization ZF Cui, YL Du, HS Zong International Journal of Modern Physics: Conference Series 29, 1460232, 2014 | 23 | 2014 |
| Susceptibilities and critical exponents within the Nambu–Jona-Lasinio model YL Du, Y Lu, SS Xu, ZF Cui, C Shi, HS Zong International Journal of Modern Physics A 30 (34), 1550199, 2015 | 15 | 2015 |
| Revisiting heavy quark radiative energy loss in nuclei within the high-twist approach YL Du, Y He, XN Wang, H Xing, HS Zong Physical Review D 98 (5), 054015, 2018 | 8 | 2018 |
| 基于有效场论的 QCD 相图研究 杜轶伦， 李程明， 史潮， 徐书生， 严妍， 张正 核技术 46 (4), 040009, 2023 | 5 | 2023 |
| Classification of quark and gluon jets in hot QCD medium with deep learning YL Du, D Pablos, K Tywoniuk arXiv preprint arXiv:2112.00681, 2021 | 5 | 2021 |
| Identifying the nature of the QCD transition in heavy-ion collisions with deep learning YL Du, K Zhou, J Steinheimer, LG Pang, A Motornenko, HS Zong, ... Nuclear Physics A 1005, 121891, 2021 | 3 | 2021 |
| Jet tomography in hot QCD medium with deep learning YL Du, D Pablos, K Tywoniuk arXiv preprint arXiv:2112.00679, 2021 | 2 | 2021 |
| Heavy flavor-asymmetric pseudoscalar mesons on the light front C Shi, P Liu, YL Du, W Jia Physical Review D 110 (9), 094010, 2024 | 1 | 2024 |
| Quark Self-Energy and Condensates in NJL Model with External Magnetic Field J Liu, Y Du, S Shi Symmetry 13 (8), 1410, 2021 | 1 | 2021 |
| Discussion on Lorentz invariance violation of noncommutative field theory and neutrino oscillation CB Luo, S Shi, YL Du, YL Wang, HS Zong International Journal of Modern Physics A 32 (06n07), 1750040, 2017 | 1 | 2017 |
| Deep Learning the Forecast of Galactic Cosmic-Rays Spectra YL Du, X Song, X Luo arXiv preprint arXiv:2410.21046, 2024 | | 2024 |
| Overview: Jet quenching with machine learning YL Du arXiv preprint arXiv:2308.10035, 2023 | | 2023 |
| PoS (HardProbes2023) 030 Overview: Jet quenching with machine learning YL Du | | 2023 |
| Applications of deep learning in jet quenching TK DU Yi-Lun, PABLOS Daniel SCIENTIA SINICA Physica, Mechanica & Astronomica 52 (5), 252017, 2022 | | 2022 |
Zhu-Fang CuiNanjing UniversityAdresse e-mail validée de nju.edu.cn