4 citations · 16 across the 24 of their papers we have counts for
3 papers · 1 filter
AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios
Zhongzhan Huang, Mingfu Liang, Shanshan Zhong +1
We propose the attention-inspired numerical solver (AttNS), a concise method that helps the generalization and robustness issues faced by the AI-Hybrid numerical solver in solving…
Deepening Neural Networks Implicitly and Locally via Recurrent Attention Strategy
Shanshan Zhong, Wushao Wen, Jinghui Qin +1
More and more empirical and theoretical evidence shows that deepening neural networks can effectively improve their performance under suitable training settings. However, deepening…
Mix-Pooling Strategy for Attention Mechanism
Shanshan Zhong, Wushao Wen, Jinghui Qin
Recently many effective attention modules are proposed to boot the model performance by exploiting the internal information of convolutional neural networks in computer vision. In…