Layer attention. by Zheng Ye (15102)

Subjects:

Self-attention upsampling layer. by Xiao Wang (19312)

Matrix crosslinking decreases cell migration persistence. by Michael Pamonag (12295175)

The architecture of the multi-head attention layer. by Guiyan Zhao (1304901)

Influence of attention layer (In%). by Hanadi Hakami (20570986)

Investigating the contributions of substructure-attention mechanism and co-attention layer. by Mei Ma (2271595)

Analysis of the substructure attention mechanism (SA) and co-attention layer (CA). by Mei Ma (2271595)

3 × 3 Attention Flow, 2 layers. by Jens Rahnfeld (21095109)

Mixed attention mechanism layers. by Jinfeng Feng (22298382)

Two-stage attention layer process. by Peijian Jin (22265437)

“…The outputs from the two branches are fused using weighted integration and passed through a fully connected layer to generate the final SOH estimate. Comparative experiments with four baseline models demonstrate that the proposed time–frequency fusion architecture significantly enhances prediction accuracy, and that each component makes a meaningful contribution to the overall performance.…”

Top half shows a bird’s eye view of the attention distribution of the different attention heads in two different layers of EnhancerBERT, the columns represent attention heads of ea... by Yansong Wang (1955323)

Structure of channel attention. by Hangchuan Zhang (13906524)

Cross-attention structure. by Hangchuan Zhang (13906524)

Decrease of injuries. by Petr Fulin (8380320)

Subjects:

Attention component comparison. by Zheng Ye (15102)

Subjects:

Networks favouring more connected individuals results in a significant decrease to the likelihood of network recovery. by Adam Lee Miles (14123916)

The significance analysis among different methods. by Ting Ruan (546739)

Attention weight analysis. by Yuhao Gong (4788654)

Subjects: “…interpretable prediction layer…”

The convolutional layer. by Yuping Yin (3617510)

The overall structural of the criss-cross attention mechanism. by Bo Liu (127343)