5 papers
Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
Hongyu Chen, David Simchi-Levi, Ruoxuan Xiong
Estimating population quantities such as mean outcomes from user feedback is fundamental to platform evaluation and social science, yet feedback is often missing not at random (MNA…
Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness
Zihan Liang, Ziwen Pan, Ruoxuan Xiong
Multimodal clinical records contain structured measurements and clinical notes recorded over time, offering rich temporal information about the evolution of patient health. Yet the…
Can We Validate Counterfactual Estimations in the Presence of General Network Interference?
Sadegh Shirani, Yuwei Luo, William Overman +2
Randomized experiments have become a cornerstone of evidence-based decision-making in contexts ranging from online platforms to public health. However, in experimental settings wit…
Causal Representation Learning from Multimodal Clinical Records under Non-Random Modality Missingness
Zihan Liang, Ziwen Pan, Ruoxuan Xiong
Clinical notes contain rich patient information, such as diagnoses or medications, making them valuable for patient representation learning. Recent advances in large language model…
Higher-Order Causal Message Passing for Experimentation with Complex Interference
Mohsen Bayati, Yuwei Luo, William Overman +2
Accurate estimation of treatment effects is essential for decision-making across various scientific fields. This task, however, becomes challenging in areas like social sciences an…