3 papers
cs.LG2024
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling
Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang +4
Uplift modeling aims to measure the incremental effect, which we call uplift, of a strategy or action on the users from randomized experiments or observational data. Most existing…
q-fin.RM2024
Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao +3
User financial default prediction plays a critical role in credit risk forecasting and management. It aims at predicting the probability that the user will fail to make the repayme…
cs.LG2023
Adversarially Robust Neural Architecture Search for Graph Neural Networks
Beini Xie, Heng Chang, Ziwei Zhang +5
Graph Neural Networks (GNNs) obtain tremendous success in modeling relational data. Still, they are prone to adversarial attacks, which are massive threats to applying GNNs to risk…