The Inter-Edge Encoder first utilizes a dual graph convolutional network (DGC) to obtain new edge embeddings of the original graph G. Then the dimension of edge embeddings is transformed to 1 by MLP to obtain edge weights denoted by weight matrix E. Weight matrix E can be used to control the weights of the neighborhood nodes to the target node during neighborhood aggregation. By increasing the weights between intra-class nodes and reducing the weights between inter-class nodes, the consistency of intra-class nodes and the difference of inter-class nodes can be strengthened. Therefore, weight matrix E can play the role of gating. Weight matrix E can be named the gated attention (GA) matrix. 解释这句话
时间: 2024-04-28 20:27:15 浏览: 5
这段话是在介绍Inter-Edge Encoder(一种用于图像分类的深度学习模型)中的关键步骤。具体来说,该模型首先使用双图卷积网络(DGC)对原始图G进行处理,得到新的边嵌入(edge embeddings)。接着,使用多层感知机(MLP)将边嵌入的维度转换为1,得到边权重矩阵E。该矩阵可以用来控制邻域聚合(neighborhood aggregation)过程中目标节点和邻居节点之间的权重。通过增加类内节点之间的权重,减少类间节点之间的权重,可以增强类内节点的一致性和类间节点的差异性。因此,矩阵E可以起到门的作用,控制邻域节点的权重分配。矩阵E也可以被称为门控注意力(gated attention,GA)矩阵,因为它可以控制注意力的分配。总之,这段话是在说明矩阵E在Inter-Edge Encoder中的作用和意义。
相关问题
https://unpkg.com/g722-encoder/dist/g722-encoder.umd.js没有这个啊
很抱歉,可能是我之前的信息有误。目前在 unpkg.com 上似乎没有 `g722-encoder` 的 UMD 构建版本。您可以考虑使用其他 npm 包管理器提供的 UMD 构建版本,例如 jsDelivr:
```html
<script src="https://cdn.jsdelivr.net/npm/g722-encoder/dist/g722-encoder.umd.js"></script>
```
或者,您可以使用 npm 安装 `g722-encoder` 包并使用模块化的方式来导入和使用它:
```javascript
// 使用 npm 安装 g722-encoder 包
$ npm install g722-encoder
// 在代码中导入 g722-encoder 包
import G722Encoder from 'g722-encoder';
```
希望这次回答能够帮到您。
whats the basic frame of u-net
The basic frame of U-Net is an encoder-decoder architecture where the encoder downsamples the input and extracts its features, and the decoder upsamples the features and produces the output. The architecture also includes skip connections to allow information to flow from the encoder to the decoder, which helps to preserve spatial information and improve performance.