Hengning Cao — accepted AI-conference papers

2022

Disentangled Spatiotemporal Graph Generative Models

Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao

AAAI 2022technical

Spatiotemporal graph represents a crucial data structure where the nodes and edges are embedded in a geometric space and their attribute values can evolve dynamically over time. Nowadays, spatiotemporal graph data is becoming increasingly popular and important, ranging from microscale (e.g. protein…

Cited by 29 Source ↗PDF ↗Scholar ↗

2021

GraphGT: Machine Learning Datasets for Graph Generation and Transformation

Yuanqi Du, Shiyu Wang, Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang +3

NeurIPS 2021poster

Graph generation has shown great potential in applications like network design and mobility synthesis and is one of the fastest-growing domains in machine learning for graphs. Despite the success of graph generation, the corresponding real-world datasets are few and limited to areas such as molecule…

Cited by 54 Source ↗code ↗Scholar ↗