3 papers
cs.NI2026
NetCause: Counterfactual Learning for Root Cause Analysis in Large-Scale Networks
Fabien Chraim, Jian Zhang, Dominik Janzing +3
Can a learned model capture how faults propagate through a large-scale network and use this knowledge to causally attribute customer impact to its underlying root cause? Existing r…
cs.LG2025
Empowering GNNs for Domain Adaptation via Denoising Target Graph
Haiyang Yu, Meng-Chieh Lee, Xiang song +2
We explore the node classification task in the context of graph domain adaptation, which uses both source and target graph structures along with source labels to enhance the genera…
cs.LG2025
FRAUDGUESS: Spotting and Explaining New Types of Fraud in Million-Scale Financial Data
Robson L. F. Cordeiro, Meng-Chieh Lee, Christos Faloutsos
Given a set of financial transactions (who buys from whom, when, and for how much), as well as prior information from buyers and sellers, how can we find fraudulent transactions? I…