翻译在:2018-GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs 有一个mxnet的实现:github.com/jennyzhang02 文章贡献: 我们提出了一种新的网络结构,门注意网络(GaAN),用于图的学习。GaAN不同于传统的多头注意机制(它均衡的消耗所有的注意头),它使用一个卷积子网络来控制每个注意头...
To assist clinical diagnosis, an EEG-based deep learning frame, which is named the gated temporal-separable attention network (GTSAN), is proposed in this paper for depression recognition. GTSAN model extracts discriminative information from EEG recordings in two ways. On the one hand, the gated...
Therefore, we present a spatial-temporal gated graph attention network (ST-GGANet) to learn the spatial-temporal patterns of skeleton sequences. The proposed approach uses a lightweight self-attention-based gate layer to pay attention to the important body parts or joints of human skeleton ...
In an attempt to make Human-Computer Interactions more natural, we propose the use of Tensor Factorized Neural Networks (TFNN) and Attention Gated Tensor Factorized Neural Network (AG-TFNN) for Speech Emotion Recognition (SER) task. Standard speech representations such as 2D and 3D Mel-Spectrogram...
GenerationwithMaxout Pointer andGatedSelf-attentionNetworks-2018 任务为输入段落和答案,输出生成问题主要处理了在问题生成...self-attention和Maxout Pointer两个机制来提升文章级的问题生成效果,并首次超越了句子级的问题生成。 方法:本文主要提出了一个改进的seq2seq模型,加入了maxout pointer机制和 ...
Temporal Attention-Gated Model for Robust SequenceClassification 用于序列分类的典型技术是针对已经分割良好的序列而设计的,编辑删除嘈杂或不相关的部分。所以,这样的方法不能轻易应用于实际应用中预期的嘈杂序列。在本文中,我们介绍时间注意门控模型(TAGM)集成了注意模型和门控周期性神经网络的想法,以更好地处理噪声或...
(rTemporal convolutional networksfor action segmentation and detection,)、核学习[20](i, Large scale online multiple kernel regression withapplication to time-series prediction, )和transformer[21]( Attend and diagnose: clinicaltime series analysis using attention models, i)的新应用,在时间序列建模方面...
In order to improve the accuracy of traffic flow prediction, a gated attention graph convolution model based on multiple spatiotemporal channels was proposed in this paper. This model takes multiple time period data as input and extracts the features of each channel by superimposing multiple gated ...
In this paper, a Bidirectional Gated Temporal Convolution Attention model is proposed for text classification, and the main works of this model are feature extraction and feature aggregation. The text features are extracted using the bidirectional temporal convolution to solve the problem that the exist...
Paper tables with annotated results for Deconstructing Recurrence, Attention, and Gating: Investigating the transferability of Transformers and Gated Recurrent Neural Networks in forecasting of dynamical systems