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An Interpretable Deep Unfolding Framework for Multi-view Representation Learning
DOI:10.1016/j.inffus.2026.104242.png)
摘要
En 中文
• 提出一种可解释的深度展开框架用于多视图表示学习
• 确保四种关键属性:一致性、拓扑结构、多样性及互补性
• 通过展开属性驱动的迭代解推导出可解释网络
Keyword:
Interpretable deep unfolding
Multi-view representation learning
Iterative solutions
Consistency
Complementarity
期刊
IF:
15.5
论文数:
4.2K
被引数:
2.7W
机构
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