interactions prediction modeling networks
16、Model_View_Delegate
QT当中model-view-delegate(模型-视图-代理)，此结构实现数据和界面的分离。Qt的模型-视图结构分为三部分：模型(model)-视图(view)-代理(Delegate)。其中模型与数据源通信；并为其它部件提供接口；视图从模型中引用数据条目的模型索引(ModelIndex)。在视 ......
论文精读：STMGCN利用时空多图卷积网络进行移动边缘计算驱动船舶轨迹预测（STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network）
《STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network》 论文链接：https://doi.org/10. ......
vue3 对子组件使用 v-model，关于绑定对象的问题
这里有最基本的使用，vue3官网 组件 v-model 我来讲讲注意事项， 如果你 v-model 的是个 reactive 创建的对象，那么将不起作用，必须得是 ref 创建的对象 要知道，v-model： <input v-model="searchText" /> <!-- 等价于 --> < ......
组件v-model
原理 当使用在一个组件上时，v-model 会被展开为如下的形式： <CustomInput :model-value="searchText" @update:model-value="newValue => searchText = newValue" /> 要让这个例子实际工作起来，<Cust ......
论文精读：基于具有时空感知的稀疏多图卷积混合网络的大数据驱动船舶轨迹预测（Big data driven trajectory prediction based on sparse multi-graph convolutional hybrid network withspatio-temporal awareness）
论文精读：基于具有时空感知的稀疏多图卷积混合网络的大数据驱动船舶轨迹预测 《Big data driven vessel trajectory prediction based on sparse multi-graph convolutional hybrid network with spati ......
[论文阅读] A unified model for multi-class anomaly detection
A unified model for multi-class anomaly detection 1 Introduction 现有方法[6, 11, 25, 27, 48, 49, 52]建议为不同类别的对象训练单独的模型，就像图1c中的情况一样。然而，这种一类一模型的方案可能会消耗大量内存，尤 ......
Retentive Networks Meet Vision Transformers， 视觉RetNet
alias: Fan2023 tags: RetNet rating: ⭐ share: false ptype: article RMT: Retentive Networks Meet Vision Transformers 初读印象 comment:: (RMT)Retentive Netwo ......
《Mamba: Linear-Time Sequence Modeling with Selective State Spaces》阅读笔记
论文标题 《Mamba: Linear-Time Sequence Modeling with Selective State Spaces》 作者 Albert Gu 和 Tri Dao 初读 摘要 Transformer 架构及其核心注意力模块 地位：目前深度学习领域普遍的基础模型。 为了解决 ......
16.What are the basic elements of an argument according to Toulmin Model? How do you evaluate evidences with the intellectual standards?
Round 1: Understanding the Basic Elements of Toulmin Model Speaker 1 (Student A): Hello, everyone! Let's start by discussing the basic elements of the ......
How to Use Docker and NS-3 to Create Realistic Network Simulations
https://insights.sei.cmu.edu/blog/how-to-use-docker-and-ns-3-to-create-realistic-network-simulations/ How to Use Docker and NS-3 to Create Realistic N ......
Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
目录概InstructRecInstruction Generation Zhang J., Xie R., Hou Y., Zhao W. X., Lin L., Wen J. Recommendation as instruction following: a large language mo ......
什么是 Web 开发的 Server Side Model
在 Web 开发中，"Server-Side Model" 是指在服务器端进行数据处理和运算的模型。这种模型的主要优点是可以处理大量数据，同时也可以利用服务器的强大计算能力。与客户端模型（如 JavaScript 中的 MVC 模型）相比，服务器端模型可以更好地保护数据和算法，因为它们不会被发送到客 ......
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations Shiru Li 1, Minzhu Xie 1, Xi ......
A novel essential protein identification method based on PPI networks and gene expression data
A novel essential protein identification method based on PPI networks and gene expression data Jiancheng Zhong 1 2, Chao Tang 1, Wei Peng 3, Minzhu Xi ......
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction Junjun Zhang 1 ......
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning Yuchi Chen 1, Minzhu Xie 1, Jie ......
Drug response prediction using graph representation learning and Laplacian feature selection
Drug response prediction using graph representation learning and Laplacian feature selection Minzhu Xie 1 2, Xiaowen Lei 3, Jianchen Zhong 3, Jianxing ......
Predict potential miRNA-disease associations based on bounded nuclear norm regularization
Predict potential miRNA-disease associations based on bounded nuclear norm regularization Yidong Rao 1, Minzhu Xie 1, Hao Wang 1 Affiliations expand P ......
LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm
LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm Minzhu Xie 1, Ruijie Xie 2, Hao Wang 3 Affiliations exp ......
Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction
Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction Junjun ......
LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier.
LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier. 作者: Lu Cuihong; Xie Minzhu 作者背景: College of Information S ......
B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm
B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm Minzhu Xie1, Hao Wang1 and Ruijie Xi1 1Hunan Normal ......
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
前置知识：【EM算法深度解析 - CSDN App】http://t.csdnimg.cn/r6TXM Motivation 目前的语义分割通常采用判别式分类器，然而这存在三个问题：这种方式仅仅学习了决策边界，而没有对数据分布进行建模；每个类仅学习一个向量，没有考虑到类内差异；OOD数据效果不好。生 ......
models补充
一、字段 1.字段列表 1 AutoField(Field) 2 - int自增列，必须填入参数 primary_key=True 3 4 BigAutoField(AutoField) 5 - bigint自增列，必须填入参数 primary_key=True 6 7 注：当model中如果没有自 ......
models简略总结
models.py文件 1 from django.db import models 2 3 # Create your models here. 4 5 class Classes(models.Model): 6 """ 7 班级表 8 """ 9 name = models.CharField ......
Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis
1 前言 1.1 标题 Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis 1.2 摘要 为了保护网络的机密性和隐私性，目前互联网上的流量被广泛地加密。然而，流量 ......
Erasing, Transforming, and Noising Defense Network for Occluded Person Re-Identification
三个分支：擦除、转换、噪声 用来生成对抗性表征，模拟遮挡问题 对应信息丢失、位置错位和噪声信息 对抗性防御：思路是GAN网络，以对抗性的方式优化生成器和判别器 ......
SPSS modeler利用类神经网络对茅台股价涨跌幅度进行预测
全文链接：https://tecdat.cn/?p=34459 原文出处：拓端数据部落公众号 分析师：Xu Zhang 数据变得越来越重要，其核心应用“预测”也成为各个行业以及产业变革的重要力量。对于股市来说，用人工智能来对股价进行预测成为量化投资的一个重要手段。本项目帮助客户运用powerBI获取 ......
2023ICCV_FSI Frequency and Spatial Interactive Learning for Image Restoration in Under-Display Cameras
三. Network 1. 2. FLB： 没看懂是怎么分离的水平和竖直方向 3. SLB：每一层保留一半的通道特征用于细化，其余的在特征重构后输出（没看懂）。 Multi-distillation Network 超分辨网络的Multi-distillation Network(2019ACMMM ......
go network poller 一
网络基础 协议架构 tcp链接 假如需要开发者去实现一套新的网络协议(例如 redis 的resp), 是基于TCP的, 那tcp这层的协议,是否需要开发者自己去实现? 这层如果自己实现, 其实很复杂, 会涉及很多算法相关. 因此, 出现了 socket 对传输层进行了抽象, 开发者不需要关注传输层 ......