Spectra-Guided Neural Tucker Factorization
This paper proposes Spectra-Guided Neural Tucker Factorization (SG-NTF) for High-Dimensional and Incomplete (HDI) tensor completion. Circumventing discrete representational limits, SG-NTF maps scalar timestamps into a continuous spectral space to abstract temporal periodicities. Concurrently, a Spatio-Temporal Co-Gating (STCG) mechanism explicitly filters latent interactions via multiplicative modulation on spatiotemporal contexts. Evaluations on real-world HDI tensors verify that SG-NTF maintains competitive completion accuracy with parameter efficiency.
| Authors | Fusheng Wang, Yikai Hou |
|---|---|
| Primary category | stat.ML |
| Published | 30 May 2026 |
| Last updated at source | 30 May 2026 |
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