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Spectra-Guided Neural Tucker Factorization

Year: 2026

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2606.00584

Authors: Wang, Fusheng, Hou, Yikai

Institutions: Chongqing University of Posts and Telecommunications, Southwest University of Political Science & Law, Southwest University

Topic: Tensor decomposition and applications

Subfield: Computational Mathematics

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: Southwest University, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities

Award: G5650156489

OpenAlex ID: W7163194945

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