IEEE

IGES-RCI: Improved Greedy Equivalence Search and Recursive Causal Inference for Industrial Equipment Failure Prediction

Abstract: Predicting equipment failures plays a pivotal role in minimizing maintenance costs and boosting production efficiency within the industrial sector. This paper introduces a novel approach ...
IEEE

CiiNet: Self-Iterative Performance Optimization for Dynamic Networks Based on Causal Inference and Interpretable Evaluation

Abstract: Causal inference and root cause analysis play a crucial role in network performance evaluation and optimization by identifying critical parameters and explaining how the configuration ...
ahajournals.org

Abstract 4368647: Improving Center Performance Assessment in Congenital Heart Surgery Through Causal Inference Weighting Approaches

Background: Traditional congenital heart surgery quality assessments rely on indirect standardization via regression, which can be complicated by heterogeneity in case-mix, surgical volume, and low ...
publichealth.jhu

The promise and pitfalls of integrating data for causal inference, with application to mental health treatment

Please join the Department of Epidemiology Center for Clinical Trials and Evidence Synthesis (CCTES) and Center for Drug Safety and Effectiveness (CDSE) in welcoming Elizabeth Stuart, PhD, AM, Chair ...
Frontiers

Correlation does not equal causation: the imperative of causal inference in machine learning models for immunotherapy

1 Department of Orthopedics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China 2 Department of Pharmacy, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, ...
publichealth.jhu

Fundamentals of Causal Inference

Please join the JHU CFAR Biostatistics and Epidemiology Methodology (BEM) Core on Thursday, September 4, 2025, from 2-3 pm ET for a session covering the fundamentals of causal inference. If you have ...
Scientific Research Publishing

Varian, H.R. (2016) Causal Inference in Economics and Marketing. Proceedings of the National Academy of Sciences of the United States of America, 113, 7310-7315.

ABSTRACT: The study focuses on identifying and distinguishing whether there are differences between those students receiving special education services later compared to their general-education peers ...
Microsoft

Improving Generative Methods for Causal Evaluation via Simulation-Based Inference

Generating synthetic datasets that accurately reflect real-world observational data is critical for evaluating causal estimators, but remains a challenging task. Existing generative methods offer a ...
Scientific Research Publishing

Hill, J.L. (2011) Bayesian Nonparametric Modeling for Causal Inference.

ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...
International Monetary Fund

A Python Package to Assist Macroframework Forecasting: Concepts and Examples

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...