3 papers
cs.LG2026
Your VAR Model is Secretly an Efficient and Explainable Generative Classifier
Yi-Chung Chen, David I. Inouye, Jing Gao
Generative classifiers, which leverage conditional generative models for classification, have recently demonstrated desirable properties such as robustness to distribution shifts.…
cs.LG2026
Using Subgraph GNNs for Node Classification:an Overlooked Potential Approach
Qian Zeng, Xin Lin, Jingyi Gao +1
Previous studies have demonstrated the strong performance of Graph Neural Networks (GNNs) in node classification. However, most existing GNNs adopt a node-centric perspective and r…
cs.LG2025
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Zeyu Zhou, Tianci Liu, Ruqi Bai +3
In high-stake domains such as healthcare and hiring, the role of machine learning (ML) in decision-making raises significant fairness concerns. This work focuses on Counterfactual…