2 papers
cs.LG2025
A Unified Invariant Learning Framework for Graph Classification
Yongduo Sui, Jie Sun, Shuyao Wang +4
Invariant learning demonstrates substantial potential for enhancing the generalization of graph neural networks (GNNs) with out-of-distribution (OOD) data. It aims to recognize sta…
stat.ME2024
Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects
Dong Yao, Caizhi Tang, Qing Cui +1
Data from observational studies (OSs) is widely available and readily obtainable yet frequently contains confounding biases. On the other hand, data derived from randomized control…