Control-based graph embeddings with data augmentation for contrastive learning
In this paper, we study the problem of unsupervised graph representation learning by
harnessing the control properties of dynamical networks defined on graphs. Our approach …
harnessing the control properties of dynamical networks defined on graphs. Our approach …
Improving Graph Machine Learning Performance Through Feature Augmentation Based on Network Control Theory
Network control theory (NCT) offers a robust analytical framework for understanding the
influence of network topology on dynamic behaviors, enabling researchers to decipher how …
influence of network topology on dynamic behaviors, enabling researchers to decipher how …