Causality-Driven Disentangled Representation Learning in Multiplex Graphs

ArXi:2603.24105v1 Announce Type: new Learning representations from multiplex graphs, i.e., multi-layer networks where nodes interact through multiple relation types, is challenging due to the entanglement of shared (common) and layer-specific (private) information, which limits generalization and interpretability. In this work, we