3 papers
cs.LG2024
UniGAD: Unifying Multi-level Graph Anomaly Detection
Yiqing Lin, Jianheng Tang, Chenyi Zi +3
Graph Anomaly Detection (GAD) aims to identify uncommon, deviated, or suspicious objects within graph-structured data. Existing methods generally focus on a single graph object typ…
cs.LG2024
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
Zinan Zheng, Yang Liu, Jia Li +2
Incorporating Euclidean symmetries (e.g. rotation equivariance) as inductive biases into graph neural networks has improved their generalization ability and data efficiency in unbo…
math.NT2023
A continuous version of multiple zeta values with double variables
Jia Li
In this paper we define a continuous version of multiple zeta functions with double variables. They can be analytically continued to meromorphic functions on with on…