Graphs, visual representations outlining the relationships between different entities, concepts or variables, can be very ...

Randomness is incredibly useful. People often draw straws, throw dice or flip coins to make fair choices. Random numbers can ...

Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania.

This paper focuses on the design of spatial experiments to optimize the amount of information derived from the experimental data and enhance the accuracy of the resulting causal effect estimator ...

How to show more historical data? Use the zoom-out option. You can add up to 100 technical indicators to your graph, such as Linear Regression, CCI, ADX, and many more. In our commitment to ...

This repository investigates how to compare causal graphs—diagrams that map out how factors influence each other—when those graphs vary in structure or in how variables are named. Drawing upon ...

Abstract: Graph Neural Network (GNN) is a popular semi-supervised graph representation learning method, whose performance strongly relies on the quality and quantity of labeled nodes. Given the ...