Abstract: This paper presents a method for creating lifted linear approximations of nonlinear graph-based models. While graph-based modeling has been successfully applied as a modular and scalable ...

Abstract: In recent years, there has been a growing interest in graph signal processing due to its capability to model and analyze irregular data generated by wireless sensor networks (WSNs).

Welcome to the repository accompanying the paper Exploring the Potential of Graph Neural Networks-based Methods for General Linear Program. This project features a website that demonstrates how ...

1 MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom 2 Department of Psychology and York Biomedical Research Institute, University of York, York, United Kingdom ...

This repo hosts the code for paper "Nonlinear Locality-Preserving Projections With Dynamic Graph Learning, in TNNLS-2025". The proposed method addresses two main limitations: first, the pre-designed ...

Capture relationships between data sets by graphing linear equations in Microsoft Excel 2007. Linear equations allow you to predict values within your data set and view the overall trend. Use ...

Data is rarely so uniform and predictable that plotting data points creates a perfectly linear arrangement. Scatter charts might have wildly varying plots that create a seemingly random correlation ...

A linear equation is drawn as a straight line on a set of axes. To draw the graph we need coordinates. We generate these coordinates by substituting values into the linear equation. STEP 1 - Draw a ...