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Found 4 papers, 3 papers with code
Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases
To make the analysis model applicable to more environments, we propose a noise patterns transferring model, which takes the spectrum of standard water samples in different environments as cases and learns the differences in their noise patterns, thus enabling noise patterns to transfer to unknown samples.
SCAI: A Spectral data Classification framework with Adaptive Inference for the IoT platform
To address the above issues, we propose a Spectral data Classification framework with Adaptive Inference.
Motifs-based Recommender System via Hypergraph Convolution and Contrastive Learning
Based on this, we also propose a hierarchical self-supervised learning model, which realizes two levels of self-supervised learning within and between channels, which improves the ability of self-supervised tasks to autonomously mine different levels of potential information.
MHNF: Multi-hop Heterogeneous Neighborhood information Fusion graph representation learning
Finally, a hierarchical semantic attention fusion model (HSAF) is constructed, which can efficiently integrate different-hop and different-path neighborhood information.
