98 citations · 167 across the 7 of their papers we have counts for
7 papers
Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks
Wei Chen, Chao Huang, Yanwei Yu +2
Trajectory-User Linking (TUL) is crucial for human mobility modeling by linking diferent trajectories to users with the exploration of complex mobility patterns. Existing works mai…
A Deep Learning Method for Real-time Bias Correction of Wind Field Forecasts in the Western North Pacific
Wei Zhang, Yueyue Jiang, Junyu Dong +4
Forecasts by the European Centre for Medium-Range Weather Forecasts (ECMWF; EC for short) can provide a basis for the establishment of maritime-disaster warning systems, but they c…
Multiplex Heterogeneous Graph Convolutional Network
Pengyang Yu, Chaofan Fu, Yanwei Yu +3
Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous network data, ranging from link prediction to…
Editing Out-of-domain GAN Inversion via Differential Activations
Haorui Song, Yong Du, Tianyi Xiang +3
Despite the demonstrated editing capacity in the latent space of a pretrained GAN model, inverting real-world images is stuck in a dilemma that the reconstruction cannot be faithfu…
Mutual Distillation Learning Network for Trajectory-User Linking
Wei Chen, Shuzhe Li, Chao Huang +3
Trajectory-User Linking (TUL), which links trajectories to users who generate them, has been a challenging problem due to the sparsity in check-in mobility data. Existing methods i…
Enhancing the Transferability via Feature-Momentum Adversarial Attack
Xianglong, Yuezun Li, Haipeng Qu +1
Transferable adversarial attack has drawn increasing attention due to their practical threaten to real-world applications. In particular, the feature-level adversarial attack is on…
Scalable Motif Counting for Large-scale Temporal Graphs
Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu +3
One fundamental problem in temporal graph analysis is to count the occurrences of small connected subgraph patterns (i.e., motifs), which benefits a broad range of real-world appli…