89 citations · 276 across the 19 of their papers we have counts for
5 papers · 1 filter
Continuous-Time Graph Learning for Cascade Popularity Prediction
Xiaodong Lu, Shuo Ji, Le Yu +3
Information propagation on social networks could be modeled as cascades, and many efforts have been made to predict the future popularity of cascades. However, most of the existing…
Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation
Han Huang, Leilei Sun, Bowen Du +1
Designing new molecules is essential for drug discovery and material science. Recently, deep generative models that aim to model molecule distribution have made promising progress…
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…
PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation
Mingzhe Liu, Han Huang, Hao Feng +3
Spatiotemporal data mining plays an important role in air quality monitoring, crowd flow modeling, and climate forecasting. However, the originally collected spatiotemporal data in…
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…