物理学报2023，Vol.72Issue(20)：106-113,8.DOI:10.7498/aps.72.20230896
机器学习回归不确定性揭示自驱动活性粒子的群集相变
Reveal flocking phase transition of self-propelled active particles by machine learning regression uncertainty
摘要
关键词
机器学习/相变/非平衡多体系统/逆统计问题Key words
machine learning/phase transition/nonequilibrium many-body system/inverse statistical problem引用本文复制引用
郭唯琛,艾保全,贺亮..机器学习回归不确定性揭示自驱动活性粒子的群集相变[J].物理学报,2023,72(20):106-113,8.基金项目
国家自然科学基金(批准号:12275089,12075090)、广东省自然科学基金(批准号:2023A1515012800,2022A1515010449)和科技部重点研发计划(批准号:2022YFA1405304)资助的课题.Project supported by the National Science Foundation of China(Grant Nos.12275089,12075090),the Basic and Applied Research Foundation of Guangdong Province,China(Grant Nos.2023A1515012800,2022A1515010449),and the National Key Research and Development Program of China(Grant No.2022YFA1405304). （批准号:12275089,12075090）
