publichealth.jhu

Biostatistics Dept. Seminar | Space-Time-Meta Causal Inference: A Weighting Perspective

Abstract: Causal inference with spatial, temporal, and meta-analytic data commonly defaults to regression modeling. While widely accepted, such regression approaches can suffer from model ...
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 ...
IEEE

Causal Inference Via Style Bias Deconfounding for Domain Generalization

Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...
GitHub

Causal Inference and Discovery in Python

What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...
eLife

Correlation detection as a stimulus computable account for audiovisual perception, causal inference, and saliency maps in mammals

Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of ...
jech.bmj

Causal mediation approaches for understanding pathways to inequalities and policy entry points: examples from early years health and development

The reduction of health inequalities has been a priority of researchers, decision-makers and practitioners for many years. Advances in causal mediation analysis offer great promise for identifying ...
Frontiers

Urban mobility and crime: causal inference using street closures as an instrumental variable

The advent of widely available cell phone mobility data in the United States has rapidly expanded the study of everyday mobility patterns in social science research. A wide range of existing ...
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 ...
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 ...