Symmetry-inducedDisentanglementonGraphs
–Neural Information Processing Systems
Disentanglementhasbeen formalized using a symmetry-centric notion for unstructured spaces, however, graphs have eluded a similarly rigorous treatment. We fill this gap with a new notionofconditional symmetryfordisentanglement, andleveragetoolsfromLie algebras toencode graph properties intosubgroups using suitable adaptations of generative models such as Variational Autoencoders.
Neural Information Processing Systems
Feb-11-2026, 22:58:36 GMT