International Monetary Fund

Can Healthy Aging Boost Labor Supply? Evidence from Korea

This paper examines the role of ‘healthy aging’ in boosting labor supply in Korea. First, we use microdata from surveys to assess whether there is evidence that the physical abilities of individuals ...
Frontiers

A causal inference method for athletic injuries based on quantile threshold functions and latent Gaussian DAG models

Introduction: Causal inference of athletic injuries provides the critical foundations for the development of effective prevention strategies. In recent years, the directed acyclic graph model (DAG) ...
IEEE

Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatiotemporal Forecasting

Abstract: Graph neural networks (GNNs), especially dynamic GNNs, have become a research hotspot in spatiotemporal forecasting problems. While many dynamic graph construction methods have been ...
IEEE

Learning Causal Structure Distributions for Robust Planning

Abstract: Structural causal models describe how the components of a robotic system interact. They provide both structural and functional information about the relationships that are present in the ...
EurekAlert!

Marriage rates and outcomes: What’s education got to do with it?

AMES, Iowa – In recent decades, a curious trend in the collective relationship status of Americans has emerged: When education levels rise in the U.S., the nation’s marriage rates fall. At first ...
Frontiers

Robot pouring: identifying causes of spillage and selecting alternative action parameters using probabilistic actual causation

1 Cognitive Neuroinformatics, University of Bremen, Bremen, Germany 2 Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany In ...
Scientific Research Publishing

Wang, X. and Shen, H.W. (2022) Gnninterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks. arXiv: 2209.07924.

ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...
Microsoft

Causal Inference Using LLM-Guided Discovery

At the core of causal inference lies the challenge of determining reliable causal graphs solely based on observational data. Since the well-known backdoor criterion depends on the graph, any errors in ...