2 papers
cs.LG2024
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
Qitian Wu, Wentao Zhao, Chenxiao Yang +5
Learning representations on large-sized graphs is a long-standing challenge due to the inter-dependence nature involved in massive data points. Transformers, as an emerging class o…
cs.LG2024
Handling Distribution Shifts on Graphs: An Invariance Perspective
Qitian Wu, Hengrui Zhang, Junchi Yan +1
There is increasing evidence suggesting neural networks' sensitivity to distribution shifts, so that research on out-of-distribution (OOD) generalization comes into the spotlight.…