3 papers
cs.LG2025
Draw a Portrait of Your Graph Data: An Instance-Level Profiling Framework for Graph-Structured Data
Tianqi Zhao, Russa Biswas, Megha Khosla
Graph machine learning models often achieve similar overall performance yet behave differently at the node level, failing on different subsets of nodes with varying reliability. St…
cs.SI2025
Population-Scale Network Embeddings Expose Educational Divides in Network Structure Related to Right-Wing Populist Voting
Malte Lüken, Javier Garcia-Bernardo, Sreeparna Deb +2
Administrative registry data can be used to construct population-scale networks whose ties reflect shared social contexts between persons. With machine learning, such networks can…
cs.LG2024
GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification
Tianqi Zhao, Megha Khosla
Graph neural networks (GNNs) have emerged as powerful models for learning representations of graph data showing state of the art results in various tasks. Nevertheless, the superio…