研究者首先提出了门控注意力单元(Gated Attention Unit, GAU),这是一个比 Transformers 更简单但更强的层。虽然 GAU 在上下文长度上依然具有二次复杂度,但它在下文展示的近似方法中更可取。 相关的层包括如下: 原版多层感知机(Vanilla MLP); 门控线性单元(Gated Linear Unit, GLU),它是门控增强的改进版 MLP ...
In one aspect, one of the systems includes a neural network configured to perform the machine learning task, the neural network including one or more attentive layers that each include a gated attention unit.
linear attention的递归结构显然没有这样的机制。因此,retnet主要的工作就是在linear attention上加入了选择遗忘机制,在一定程度上弥补了这一漏洞。Retnet即是带选择遗忘机制的linear attention与Chunk-wise block-parallel attention的结合的产物。 加入遗忘门最简单的办法就是在state前面乘上一个可学习的矩阵A\in R^{...
基于Gated Attention Unit的Transformer模型(尝鲜版) 介绍 GAU-α:https://kexue.fm/archives/9052 GAU:https://kexue.fm/archives/8934 原始论文:https://arxiv.org/abs/2202.10447 评测 CLUE榜单分类任务结果 iflytektnewsafqmccmnliocnliwsccsl BERT60.0656.8072.4179.5673.9378.6283.93 ...
此外,以GaAN为构建块,构造了图形门控重电流单元Graph Gated Recurrent Unit (GGRU)来解决交通速度预测问题。对三个实际数据集的大量实验表明,我们的GaAN框架在这两个任务上都取得了最新的结果。 GaAN和GAT区别就在于--- The difference between the attention aggregator in GaAN and the one in GAT is that ...
Qin et al. (2021) adopted the attention mechanism to focus on the reset gate and update gate of GRU which contain short- and long-term information, respectively, and named it the gated attention unit. Moreover, they further proposed a gated dual attention unit (GDAU), which fused the ...
we introduce Gated Attention Coding (GAC), aplug-and-play modulethat leverages the multi-dimensional gated attention unit to efficiently encode inputs into powerful representations before feeding them into the SNN architecture. GAC functions as apreprocessing layerthat does not disrupt the spike-driven...
In this paper, we propose an attention aware bidirectional GRU (Bi-GRU) framework to classify the sentiment polarity from the aspects of sentential-sequence modeling and word-feature seizing. It is composed of a pre-attention Bi-GRU to incorporate the complicated interaction between words by ...
Prediction of air pollutant concentrations based on TCN-BiLSTM-DMAttention with STL decomposition. Sci. Rep. 13, 4665 (2023). Article ADS CAS PubMed PubMed Central Google Scholar Yang, L. & Dong, H. Robust support vector machine with generalized quantile loss for classification and regression...
To address the above mentioned issues, a physics-informed gated recurrent graph attention unit network (PGRGAT) is proposed, which consists of two co-trained components: a physics-informed graph structure learning module (PGSL) and a gated recurrent graph attention unit (GRGAU) network. To learn...