98 citations · 98 across the 4 of their papers we have counts for
5 papers
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…
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…
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…
NetInfoF Framework: Measuring and Exploiting Network Usable Information
Meng-Chieh Lee, Haiyang Yu, Jian Zhang +5
Given a node-attributed graph, and a graph task (link prediction or node classification), can we tell if a graph neural network (GNN) will perform well? More specifically, do the g…
NetSimile: A Scalable Approach to Size-Independent Network Similarity
Michele Berlingerio, Danai Koutra, Tina Eliassi-Rad +1
Given a set of k networks, possibly with different sizes and no overlaps in nodes or edges, how can we quickly assess similarity between them, without solving the node-corresponden…