Causality-Driven Disentangled Representation Learning in Multiplex Graphs
Causality-Driven Disentangled Representation Learning in Multiplex Graphs explores A causal inference framework to disentangle shared and private information in multiplex graphs for improved representation learning.. Commercial viability score: 5/10 in Graph Representation Learning.
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