text-to-image reinforcement pre-trained generate
The importance of experience replay database composition in deep reinforcement learning
![](https://img2023.cnblogs.com/blog/1428973/202307/1428973-20230727110633815-1407402877.png) **发表时间:**2015(Deep Reinforcement Learning Workshop, NIPS ......
SpringBoot项目集成Mybatis Generator代码生成器
# 添加依赖 在项目的pom.xml文件中添加以下依赖 ``` org.mybatis.generator mybatis-generator-maven-plugin 1.4.0 src/main/resources/generator/generator-config.xml true true ......
概述增强式学习(Reinforcement Learning)
概述增强式学习(Reinforcement Learning) Supervised Learning(自监督学习):告诉机器输入和输出,用有标注的训练资料训练出的Network Reinforcement Learning(增强式学习):给机器一个输入,我们不知道最佳输出是什么(适用于标注困难或者 ......
cpp generate uuid via rand() and test speed which is 4 times+ faster than libuuid
// main.cpp #include <algorithm> #include <chrono> #include <cstdio> #include <cstdlib> #include <cstdint> #include <ctime> #include <fstream> #includ ......
mybatis的generator 代码生成器(自动生成DAO,PO,XML)
### 1. 引入 插件 ``` java org.mybatis.generator mybatis-generator-maven-plugin 1.3.5 src/main/resources/generatorMapper.xml true true ``` 刷新下pop ### 2.配置下 ......
mybatis-plus-generator-ui可视化生成mybatis plus+MVC代码
mybatis-plus-generator-ui可视化生成mybatis plus+MVC代码 https://github.com/davidfantasy/mybatis-plus-generator-ui 引入依赖 ``` com.github.davidfantasy mybatis-pl ......
cpp generate uuid by random
#include <cstdio> #include <cstdlib> #include <ctime> #include <cstdint> uint32_t rand32() { return ((rand() & 0x3) << 30) | ((rand() & 0x7fff) << 15) ......
REALM Retrieval-Augmented Language Model Pre-Training
[TOC] > [Guu K., Lee K., Tung Z., Pasupat P. and Chang M. REALM: Retrieval-augmented language model pre-training. ICML, 2020.](http://arxiv.org/abs/20 ......
cpp generate random array and then quick sort
#include <algorithm> #include <chrono> #include <ctime> #include <fstream> #include <iomanip> #include <iostream> #include <random> #include <sstream> ......
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
[TOC] > [Lewis P. and Perez E., et al. Retrieval-augmented generation for knowledge-intensive nlp tasks. NIPS, 2020.](http://arxiv.org/abs/2005.11401) ......
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
图的作用: 图结构捕捉不同类型节点(即用户、项目和属性)之间丰富的关联信息,使我们能够发现协作用户对属性和项目的偏好。因此,我们可以利用图结构将推荐和对话组件有机地整合在一起,其中对话会话可以被视为在图中维护的节点序列,以动态地利用对话历史来预测下一轮的行动。 由四个主要组件组成:基于图的 MDP ......
粗读Multi-Task Recommendations with Reinforcement Learning
论文: Multi-Task Recommendations with Reinforcement Learning 地址: https://arxiv.org/abs/2302.03328 # 摘要 In recent years, Multi-task Learning (MTL) has yi ......
MyBatis Generator代码生成器
地址:http://mybatis.org/generator/quickstart.html 依赖 <!--mybatis代码生成--> <dependency> <groupId>org.mybatis.generator</groupId> <artifactId>mybatis-genera ......
[论文阅读] CF-Font@ Content Fusion for Few-shot Font Generation
## 1. Pre title: CF-Font: Content Fusion for Few-shot Font Generation accepted: CVPR2023 paper: https://arxiv.org/abs/2303.14017 | https://openaccess. ......
Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics
在Delta Lake官网上提到的一篇新一代湖仓架构的论文. ![image.png](https://cdn.nlark.com/yuque/0/2023/png/492896/1689406041936-82416672-e4d8-46db-9742-19b4a283b7f4.png#avera ......
mybatis-generator 代码生成工具
官网文档:http://mybatis.org/generator/quickstart.html 引入依赖: <!-- 代码生成工具https://mvnrepository.com/artifact/org.mybatis.generator/mybatis-generator-core --> ......
Fiori:Open Application Generator
请按照Sinead Roche指定的以下步骤进行操作 - 使用以下命令卸载现有生成器:npm uninstall -g @sap/generator-fiori。 然后尝试通过执行以下命令再次安装生成器:npm i -g @sap/generator-fiori 应用程序生成器未被打开 |SAP 社 ......
CoDi: Any-to-Any Generation via Composable Diffusion
我们介绍了一种名为可组合扩散(CoDi)的新型生成模型,能够从任意输入模态的任意组合中生成任意组合的输出模态,例如语言、图像、视频或音频。与现有的生成人工智能系统不同,CoDi能够同时生成多个模态,并且其输入不限于文本或图像等子集模态。尽管许多模态组合缺乏训练数据集,我们提出在输入和输出空间中对模态 ......
go generate命令简介
最近在研究[kratos](https://github.com/go-kratos/kratos)的使用,发现在`kratos run`之前会先运行`go generate ./...`命令。 这个命令之前没怎么用过,所以决定学习下该命令的用法。 `go generate`是Go语言中的一个命令, ......
Regret Minimization Experience Replay in Off-Policy Reinforcement Learning
**发表时间:**2021 (NeurIPS 2021) **文章要点:**理论表明,更高的hindsight TD error,更加on policy,以及更准的target Q value的样本应该有更高的采样权重(The theory suggests that data with highe ......
《Generative Agents: Interactive Simulacra of Human Behavior》论文学习
一、论文基本思想 Figure 1: Generative agents create believable simulacra of human behavior for interactive applications. In this work, we demonstrate generati ......
python: generate and decode QrCode
# encoding: utf-8 #-*- coding: UTF-8 -*- # 版权所有 2023 ©涂聚文有限公司 # 许可信息查看: # 描述: # Author : geovindu,Geovin Du 涂聚文. # IDE : PyCharm 2023.1 python 311 # D ......
argocd + kustomize 报错“rpc error: code = Unknown desc = Manifest generation error (cached)”
argocd + kustomize 报错“rpc error: code = Unknown desc = Manifest generation error (cached)” 报错内容 报错内容为:rpc error: code = Unknown desc = Manifest genera ......
Effective Diversity in Population-Based Reinforcement Learning
![](https://img2023.cnblogs.com/blog/1428973/202307/1428973-20230707084258489-1960518081.png) **发表时间:**2020 (NeurIPS 2020) **文章要点:**这篇文章提出了Diversity v ......
Mybatis-generator插件快速生成代码
生成步骤: 1. 在pom.xml中添加插件 ``` org.mybatis.generator mybatis-generator-maven-plugin 1.4.0 com.dm dmjdbc8 1.8.0 true true ``` 2. 对generatorConfig.xml文件进行配置 ......
2023-05-20-Probability-Generating-Function
abbrlink: PGF categories: [] date: '2023-05-20T15:25:06.983219+08:00' tags: - 数学 title: 「Note」Probability Generating Function toc: true updated: 2023- ......
2023-06-04-Generating-Function-Editor
abbrlink: '' categories: [] date: '2023-06-04T17:28:44.630973+08:00' tags: - math title: 「Study」Generating Function Editor toc: true updated: 2023-6-5 ......
Spectrum Random Masking for Generalization in Image-based Reinforcement Learning
郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! ......
DreamBooth Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
[TOC] > [Ruiz N., Li Y., Jampani V., Pritch Y., Rubinstein M. and Aberman K. DreamBooth: Fine tuning text-to-image diffusion models for subject-driven ......
Faster sorting algorithms discovered using deep reinforcement learning
## 摘要: - `AlphaDev`模型优化排序算法,将排序算法提速70%。通过强化学习,AlphaDev发现了更加有效的算法,直接超越了科学家和工程师们几十年来的精心打磨。现在,新的算法已经成为两个标准C++编码库的一部分,每天都会被全球的程序员使用数万亿次。 ## 介绍 - 优化目标为排序算法 ......