3 citations · 3 across the 2 of their papers we have counts for
5 papers · 1 filter
Learn When and Where to Connect: Adaptive Virtual Nodes for Dynamic Message Passing on Graphs
Jaejun Lee, Joyce Jiyoung Whang
While Virtual Nodes (VNs) are often utilized in Message Passing Neural Networks (MPNNs) to facilitate effective message passing, existing VN-based methods have limitations, such as…
Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion
Jaejun Lee, Seheon Kim, Joyce Jiyoung Whang
Hyper-relational knowledge graphs (HKGs) effectively represent complex facts. While inferring new knowledge in HKGs is a critical problem, current methods cast it as a simple link…
Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors
Jinhyeok Choi, Heehyeon Kim, Joyce Jiyoung Whang
Graph neural networks (GNNs) have emerged as an effective tool for fraud detection, identifying fraudulent users, and uncovering malicious behaviors. However, attacks against GNN-b…
SpoT-Mamba: Learning Long-Range Dependency on Spatio-Temporal Graphs with Selective State Spaces
Jinhyeok Choi, Heehyeon Kim, Minhyeong An +1
Spatio-temporal graph (STG) forecasting is a critical task with extensive applications in the real world, including traffic and weather forecasting. Although several recent methods…
Dynamic Relation-Attentive Graph Neural Networks for Fraud Detection
Heehyeon Kim, Jinhyeok Choi, Joyce Jiyoung Whang
Fraud detection aims to discover fraudsters deceiving other users by, for example, leaving fake reviews or making abnormal transactions. Graph-based fraud detection methods conside…