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CASIA OpenIR
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Computational Experiments for Complex Social Systems: Experiment Design and Generative Explanation 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 1022-1038
作者:  Xiao Xue;  Deyu Zhou;  Xiangning Yu;  Gang Wang;  Juanjuan Li;  Xia Xie;  Lizhen Cui;  Fei-Yue Wang
Adobe PDF(7239Kb)  |  收藏  |  浏览/下载：24/6  |  提交时间：2024/03/18
Agent-based modeling  computational experiments  cyber-physical-social systems (CPSS)  generative deduction  generative experiments  meta model  
Computational Experiments for Complex Social Systems: Integrated Design of Experiment System 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1175-1189
作者:  Xiao Xue;  Xiangning Yu;  Deyu Zhou;  Xiao Wang;  Chongke Bi;  Shufang Wang;  Fei-Yue Wang
Adobe PDF(11890Kb)  |  收藏  |  浏览/下载：10/3  |  提交时间：2024/04/10
Artificial society  computational experiments  model integration  operation engine  technology integration  
Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 231-239
作者:  Yahui Liu;  Bin Tian;  Yisheng Lv;  Lingxi Li;  Fei-Yue Wang
Adobe PDF(8541Kb)  |  收藏  |  浏览/下载：212/152  |  提交时间：2024/01/02
Content-based Transformer  deep learning  feature aggregator  local attention  point cloud classification  
Point Cloud Classification Using Content-based Transformer via Clustering in Feature Space 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 页码: 1-9
作者:  Yahui Liu;  Bin Tian;  Yisheng Lv;  Lingxi Li;  Feiyue Wang
Adobe PDF(4216Kb)  |  收藏  |  浏览/下载：173/64  |  提交时间：2023/05/19
A Parallel Control Method For Zero-Sum Games With Unknown Time-varying System 期刊论文
The International Journal of Intelligent Control and Systems, 2023, 页码: 5页
作者:  Qinglai Wei;  Zhenhua Zhu;  Jie Zhang;  Feiyue Wang
Adobe PDF(470Kb)  |  收藏  |  浏览/下载：110/45  |  提交时间：2023/12/15
STGSA: A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 1, 页码: 226-238
作者:  Zebing Wei;  Hongxia Zhao;  Zhishuai Li;  Xiaojie Bu;  Yuanyuan Chen;  Xiqiao Zhang;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(7068Kb)  |  收藏  |  浏览/下载：229/60  |  提交时间：2023/01/03
Deep learning  graph neural network (GNN)  multi-stream  spatial-temporal feature extraction  temporal graph  traffic prediction  
Parallel Learning: Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 3, 页码: 603-631
作者:  Qinghai Miao;  Yisheng Lv;  Min Huang;  Xiao Wang;  Fei-Yue Wang
Adobe PDF(11937Kb)  |  收藏  |  浏览/下载：777/144  |  提交时间：2023/03/02
Machine learning  parallel learning  parallel systems  sim-to-real  syn-to-real  virtual-to-real  
SST-GAN: Single Sample-based Realistic Traffic Image Generation for Parallel Vision 会议论文
, Macau, China, 2022-10-08~2022-10-12
作者:  Jiangong Wang;  Yutong Wang;  Yonglin Tian;  Xiao Wang;  Fei-Yue Wang
Adobe PDF(1971Kb)  |  收藏  |  浏览/下载：93/20  |  提交时间：2023/05/17
ShadowPainter: Active Learning Enabled Robotic Painting through Visual Measurement and Reproduction of the Artistic Creation Process 期刊论文
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2022, 卷号: 105, 期号: 3, 页码: 17
作者:  Guo, Chao;  Bai, Tianxiang;  Wang, Xiao;  Zhang, Xiangyu;  Lu, Yue;  Dai, Xingyuan;  Wang, Fei-Yue
Adobe PDF(7718Kb)  |  收藏  |  浏览/下载：249/45  |  提交时间：2022/07/25
Painting reproduction  Robotic painting  Robotic system  Vision-based measurement  
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：251/40  |  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