Causal Inference : 6th Pacific Causal Inference Conference, PCIC 2024, Shanghai, China, July 5–6, 2024, Revised Selected Papers / edited by Xiao-Hua Zhou, Jinzhu Jia.

Format:

Book

Contributor:

Zhou, Xiao-Hua, editor.

Jia, Jinzhu, editor.

Series:

Communications in Computer and Information Science, 1865-0937 ; 2200

Language:

English

Subjects (All):

Machine learning.

Artificial intelligence--Data processing.

Artificial intelligence.

Machine Learning.

Data Science.

Artificial Intelligence.

Local Subjects:

Machine Learning.

Data Science.

Artificial Intelligence.

Physical Description:

1 online resource (IX, 95 p. 20 illus., 15 illus. in color.)

Edition:

1st ed. 2025.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2025.

Summary:

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.

Contents:

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.

Notes:

Includes bibliographical references and index.

ISBN:

9789819778126

9819778123