4 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs
Kun Wang, Guibin Zhang, Xinnan Zhang +6
Graph Neural Networks (GNNs) have become pivotal tools for a range of graph-based learning tasks. Notably, most current GNN architectures operate under the assumption of homophily,…
cs.AI2023★ 4 cited
Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
Hao Wu, Yuxuan Liang, Wei Xiong +4
Efficiently modeling spatio-temporal (ST) physical processes and observations presents a challenging problem for the deep learning community. Many recent studies have concentrated…