Instrumental variables (IVs), widely applied in economics and healthcare, enable consistent
counterfactual prediction in the presence of hidden confounding factors, effectively …

Heterogeneous treatment effect (HTE) estimation is vital for understanding the change of
treatment effect across individuals or subgroups. Most existing HTE estimation methods …

A common issue in learning decision-making policies in data-rich settings is spurious
correlations in the offline dataset, which can be caused by hidden confounders. Instrumental …

While many works have studied statistical data fusion, they typically assume that the various
datasets are given in advance. However, in practice, estimation requires difficult data …

While deep neural networks have made remarkable progress in various vision tasks, their
performance typically deteriorates when tested in out-of-distribution (OOD) scenarios. Many …

As the Internet of Things (IoT) continues to revolutionize data acquisition and dissemination,
integrating monotonicity principles into data fusion (DF) processes emerges as a pivotal …