IMPRL-Net: interpretable multi-view proximity representation learning network

Author:

Lan Shiyang,Fang Zihan,Du Shide,Cai Zhiling,Wang ShipingORCID

Funder

National Natural Science Foundation of China

National Key Research and Development Plan of China

Publisher

Springer Science and Business Media LLC

Reference66 articles.

1. Wei X, Zhang Y, Wang H (2023) Joint semantic embedding with structural knowledge and entity description for knowledge representation learning. Neural Comput Appl 35(5):3883–3902

2. Zheng Q, Zhu J, Li Z, Tian Z, Li C (2023) Comprehensive multi-view representation learning. Inf Fusion 89:198–209

3. Lu W, Li D, Nie L, Jing P, Su Y (2023) Learning dual low-rank representation for multi-label micro-video classification. IEEE Trans Multimedia 25:77–89

4. Nguyen T-S, Luong M, Kaaniche M, Ngo LH, Beghdadi A (2023) A novel multi-branch wavelet neural network for sparse representation based object classification. Pattern Recogn 135:1–11

5. Wu Z, Zhang Z, Fan J (2023) Graph convolutional kernel machine versus graph convolutional networks. Adv Neural Inf Process Syst 36:1–14

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