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This work was supported in part by the Shanghai Science and Technology Innovation Action Plan Project (22511100700).
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Hongda Qi received his BS and MS degrees in computer science and technology from Shandong University of Science and Technology, China in 2015 and 2018, respectively. He is currently pursuing the PhD degree from the College of Electronic and Information Engineering, Tongji University, China. His research interests include Petri net theory and machine learning.
Changjun Jiang received the PhD degree from the Institute of Automation, Chinese Academy of Sciences, China in 1995. He is currently the leader of the Key Laboratory of Embedded System and Service Computing (Ministry of Education), Tongji University, China. He is an academician of Chinese Academy of Engineering, China and an IET Fellow and an Honorary Professor with Brunel University London, UK. He has been the recipient of one international prize and seven prizes in the field of science and technology.
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Qi, H., Jiang, C. A perspective on Petri Net learning. Front. Comput. Sci. 17, 176351 (2023). https://doi.org/10.1007/s11704-023-3381-5
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DOI: https://doi.org/10.1007/s11704-023-3381-5