… deep learning architecture that takes as input the entire dataset instead of processing one
datapoint at a time. Our approach uses self-attention … using parametric attention mechanisms. …

… self-attention mechanism, we build several SAGAN models by adding the selfattention …
As shown in Table 1, the SAGAN models with the self-attention mechanism at the middle-to-…

… of attention mechanism. Finally, we discuss the interpretability that attention brings to deep
learning … In these classification tasks, self attention is mainly used to construct more effective …

… , existing deep learning … , a deep learning framework with hybrid self-attention mechanism
to classify sleep stages from the multivariate PSG inputs. The proposed hybrid self-attention …

… In [46], the convolutional Auto-Encoder combined with self-attention has been used to reduce
the … The other deep learning method used in this work is the attention mechanism. It was …

… for a specific deep learning structure to … deep learning framework with sensor-temporal
self-attention mechanism for heterogeneous on-device sensor inputs. The proposed selfattention …

… In this study, we found that transformer and self-attention computer mechanisms are more …
In addition, we also conducted experiments on the necessity of the self-attention for the model, …

… Discussion: This study presented deep insights into integrating ensemble deep learning
with self-attention as a mechanism for predicting immunotherapy responses to human cancers, …

… novel deep learning method to automatically extract attributes of lesions of interest from
the clinical text. Different from classical CNN models, we integrated the multi-head self-attention …

… We propose a joint self-attention mechanism that not only includes an attention mechanism
… • To the best of our knowledge, we are the first research to incorporate attention mechanism …