244 citations · 684 across the 18 of their papers we have counts for
18 papers
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
Han Huang, Leilei Sun, Bowen Du +1
Learning the underlying distribution of molecular graphs and generating high-fidelity samples is a fundamental research problem in drug discovery and material science. However, acc…
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation
Han Huang, Leilei Sun, Bowen Du +2
Graph generative models have broad applications in biology, chemistry and social science. However, modelling and understanding the generative process of graphs is challenging due t…
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
Liangzhe Han, Xiaojian Ma, Leilei Sun +4
Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society. Among them, the pairwise Origin-Destination (OD) demand…
Continuous-Time User Preference Modelling for Temporal Sets Prediction
Le Yu, Zihang Liu, Leilei Sun +3
Given a sequence of sets, where each set has a timestamp and contains an arbitrary number of elements, temporal sets prediction aims to predict the elements in the subsequent set.…
Harnessing Context for Budget-Limited Crowdsensing with Massive Uncertain Workers
Feng Li, Jichao Zhao, Dongxiao Yu +2
Crowdsensing is an emerging paradigm of ubiquitous sensing, through which a crowd of workers are recruited to perform sensing tasks collaboratively. Although it has stimulated many…
Heterogeneous Graph Representation Learning with Relation Awareness
Le Yu, Leilei Sun, Bowen Du +3
Representation learning on heterogeneous graphs aims to obtain meaningful node representations to facilitate various downstream tasks, such as node classification and link predicti…