Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024
Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts
Lanting Fang, Yulian Yang, Yawei Zhang +3
Continuous-Time Dynamic Graphs (CTDGs) enable fine-grained modeling of evolving relational systems. However, most existing CTDG representation learning methods are tailored to in-d…
cs.LG2024
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Shuo Liu, Di Yao, Lanting Fang +5
Detecting anomaly edges for dynamic graphs aims to identify edges significantly deviating from the normal pattern and can be applied in various domains, such as cybersecurity, fina…