1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning
Xinxun Zhang, Pengfei Jiao, Mengzhou Gao +2
Although dynamic graph neural networks (DyGNNs) have demonstrated promising capabilities, most existing methods ignore out-of-distribution (OOD) shifts that commonly exist in dynam…
cs.LG2025★ 1 cited
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
Zehao Liu, Mengzhou Gao, Pengfei Jiao
Multivariate time series anomaly detection has numerous real-world applications and is being extensively studied. Modeling pairwise correlations between variables is crucial. Exist…
cs.LG2024
Informative Subgraphs Aware Masked Auto-Encoder in Dynamic Graphs
Pengfe Jiao, Xinxun Zhang, Mengzhou Gao +2
Generative self-supervised learning (SSL), especially masked autoencoders (MAE), has greatly succeeded and garnered substantial research interest in graph machine learning. However…