Graphical representation— Histogram ... Variance and standard deviation— determination and comparison. Correlation and regression. Probability : Random experiment, outcomes and associated ...

Finally, the GCN-BiGRU network is compared with Castagna’s empirical velocity formula, support vector regression ... graph domain by mapping their dependencies with the TIC. TIC is a noise-robust ...

A multi-dimensional mathematical theory applied to texts belonging to the classical Greek Literature spanning eight centuries ...

Inspired by dynamic Graph neural networks, we propose a Group-aware Dynamic Graph Representation Learning (GDGRL) method for next POI recommendation. GDGRL connects different user sequences and ...

To tackle these challenges, we propose a novel framework called AISFuser to i) encode unique maritime traffic network into graphical representations, and ii) introduce the heterogeneity into ...

A non-linear model and regression were used to quantitatively assess the ... The study further explores how hippocampal neural representations are altered over time, showing that these representations ...

This paper hopes to promote the research in this field by exploring the simple linear graph neural network and achieve the representation learning effect equivalent to the current model. Among them, ...