Causal Inference
Description
This book constitutes the revised selected papers of the 6th Pacific Causal Inference Conference, PCIC 2024, held in Shanghai, China, during July 5-6, 2024.
The 8 papers included in these proceedings were carefully reviewed and selected from 15 submissions. They aim to promote research and developmental activities in the fields of Causal Inference and Artificial Intelligence.
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Content
Avoiding the Unconfoundednes Assumption: Counterfactual Inference Considering Unobserved Confounders.-Causal Inference in the Multiverse of Hazard.- A Continuous Structural Intervention Distance to Compare Causal Graphs.- Detection Windows from Hidden Markov Model for Discovering Varying Causal Relations Between Time Series.- Endogenous Confounding in Causal Decomposition Analysis.- Evaluation Criteria for Causal Discovery Without Ground-truth Graphs.- Optimizing Experimental Design for Causal Effect Estimation with Partial Measurements.- Exploring the Use of Q-learning in Causal Inference for Adaptive Interventions.
