1 code implementation • 11 Feb 2024 • Fangyu Ding, Haiyang Wang, Zhixuan Chu, Tianming Li, Zhaoping Hu, Junchi Yan
Many recent endeavors of GIL focus on extracting the invariant subgraph from the input graph for prediction as a regularization strategy to improve the generalization performance of graph learning.
no code implementations • 29 Sep 2021 • Liangliang Shi, Fangyu Ding, Junchi Yan, Yanjie Duan, Guangjian Tian
Despite the fast advance in neural temporal point processes (NTPP) which enjoys high model capacity, there are still some standing gaps to fill including model expressiveness, predictability, and interpretability, especially with the wide application of event sequence modeling.