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Black swan event small-sample transfer learning (BEST-L) and its case study on electrical power prediction in COVID-19 期刊论文
APPLIED ENERGY, 2022, 卷号: 309, 页码: 10
作者:  Hu, Chenxi;  Zhang, Jun;  Yuan, Hongxia;  Gao, Tianlu;  Jiang, Huaiguang;  Yan, Jing;  Gao, David Wenzhong;  Wang, Fei-Yue
收藏  |  浏览/下载：186/0  |  提交时间：2022/07/25
Transfer learning  Black swan event  Small-sample learning  COVID-19  Load forecasting  
HackGAN: Harmonious Cross-Network Mapping Using CycleGAN With Wasserstein-Procrustes Learning for Unsupervised Network Alignment 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2022, 页码: 14
作者:  Yang, Linyao;  Wang, Xiao;  Zhang, Jun;  Yang, Jun;  Xu, Yancai;  Hou, Jiachen;  Xin, Kejun;  Wang, Fei-Yue
Adobe PDF(4053Kb)  |  收藏  |  浏览/下载：289/46  |  提交时间：2022/03/17
Task analysis  Optimization  Generative adversarial networks  Computational modeling  Automation  Training  Standards  Embedding  generative adversarial network  network alignment (NA)  optimal transport  unsupervised learning