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cs.SI2026
A Network Science Perspective on Evaluating Deep Graph Generative Models
Tianrui Mao, Abele Malan, Megha Khosla +2
Traditional network models from network science, such as the Erdos-Renyi and configuration models, generate random networks that reproduce few selected topological properties obser…
cs.SI2018
Node Representation Learning for Directed Graphs
Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl +1
We propose a novel approach for learning node representations in directed graphs, which maintains separate views or embedding spaces for the two distinct node roles induced by the…