40 citations · 47 across the 5 of their papers we have counts for
5 papers
Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction
Tao Zou, Le Yu, Leilei Sun +3
Accurate prediction of what types of patents that companies will apply for in the next period of time can figure out their development strategies and help them discover potential p…
Towards Better Dynamic Graph Learning: New Architecture and Unified Library
Le Yu, Leilei Sun, Bowen Du +1
We propose DyGFormer, a new Transformer-based architecture for dynamic graph learning. DyGFormer is conceptually simple and only needs to learn from nodes' historical first-hop int…
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
Ruixing Zhang, Liangzhe Han, Boyi Liu +2
Recent years have witnessed a rapid growth of applying deep spatiotemporal methods in traffic forecasting. However, the prediction of origin-destination (OD) demands is still a cha…
Label-Enhanced Graph Neural Network for Semi-supervised Node Classification
Le Yu, Leilei Sun, Bowen Du +2
Graph Neural Networks (GNNs) have been widely applied in the semi-supervised node classification task, where a key point lies in how to sufficiently leverage the limited but valuab…
Exploiting Global and Local Hierarchies for Hierarchical Text Classification
Ting Jiang, Deqing Wang, Leilei Sun +3
Hierarchical text classification aims to leverage label hierarchy in multi-label text classification. Existing methods encode label hierarchy in a global view, where label hierarch…