Patent classification aims to assign multiple International Patent
Class...
Designing new molecules is essential for drug discovery and material sci...
We propose DyGFormer, a new Transformer-based architecture for dynamic g...
Spatiotemporal data mining plays an important role in air quality monito...
Learning the underlying distribution of molecular graphs and generating
...
Graph generative models have broad applications in biology, chemistry an...
The essential task of urban planning is to generate the optimal land-use...
Traditional urban planning demands urban experts to spend considerable t...
Traffic demand forecasting by deep neural networks has attracted widespr...
Recent studies have shown great promise in applying graph neural network...
Graph Neural Networks (GNNs) have been widely applied in the semi-superv...
Recent years have witnessed a rapid growth of applying deep spatiotempor...
Hierarchical text classification aims to leverage label hierarchy in
mul...
Given a sequence of sets, where each set is associated with a timestamp ...
Urban planning designs land-use configurations and can benefit building
...
Mechanical analysis for the full face of tunnel structure is crucial to
...
Representation learning on heterogeneous graphs aims to obtain meaningfu...
Extreme Multi-label text Classification (XMC) is a task of finding the m...
Heterogeneous graphs are pervasive in practical scenarios, where each gr...
Graph Convolutional Network (GCN) has been widely applied in transportat...
While Water Treatment Networks (WTNs) are critical infrastructures for l...
Given a sequence of sets, where each set contains an arbitrary number of...