A central limit theorem for an omnibus embedding of multiple random graphs and implications for multiscale network inference
Keith Levin, Avanti Athreya, Minh Tang, Vince Lyzinski, Youngser Park, Carey E. Priebe
Paper
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arXiv preprint arXiv:1705.09355, 2022
Notes
The Omnibus embedding is cited in riva2026random alongside UASE as an existing joint embedding approach that fails to address our obstructions, modeling activity over fixed identity rather than genuinely evolving latent positions.
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