Abstract: In recent years, network representation learning (NRL) has attracted increasing attention due to its efficiency and effectiveness to analyze network structural data. NRL aims to learn ...

Abstract: Graph Neural Networks (GNNs) update node representations through message passing ... to mitigate degree bias by discovering structural similarities between non-adjacent nodes through ...

A simplistic programming language interpreter to Python to help students grasp finite automata theory programmatically and with a computed graph through visualization libraries.

A simplistic programming language interpreter to Python to help students grasp finite automata theory programmatically and with a computed graph through visualization libraries. This project aims to ...

Traditional assessment methods often represent corrosion as uniform section loss or rely on simplified surface representations, compromising the accuracy of the residual capacity estimation. To ...

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