计算机科学 > 机器学习
[于2026年5月28日(v1)提交，最后一次修订为2026年9月8日(本版本v2).
标题：Generative AI基金会的小书：一个直观的数学基础
查看 PDF HTML( 实验)
摘要：本书为现代基因人工智能的数学基础提供了一个紧凑，以衍生为导向的介绍。 它不调查最近的每一个架构或执行细节，而是通过将遗传模型的主要家族联系起来的想法，从五氯苯甲醚、概率五氯苯甲醚、变异自编码器、扩散模型到正常流动、自动递减因子化、GANs、Wasserstein GANs和以能源为基础的模型，发展出一条连贯的路线。 目的是使基因建模的结构更容易获得，同时不去除理解这些模型的衍生和关联所需的数学物质。 该书旨在作为数学好奇的研究人员，从业者和学生的奠基入门。
提交历史
出自：天华陈 [观赏电子邮件]
[v1] Thu, 28 May 2026 10: 12:00 UTC (125 KB) (英语).
[v2] Tue, 8 September 2026 07:17:36 UTC (1,168 KB) (英语).
其他特征
参考资料和引用
正在装入。..
书目和引用工具
书目浏览器( 什么是浏览器？)
连接文件( 什么是连接文件？)
Litmaps (什么是 Litmaps? ).
点击智能引用( 什么是智能引用？
与本条有关的代码、数据和媒体
阿尔法XIV (什么是AlphaXiv吗？)
文档的催化X代码查找器( 什么是催化X?)
DagsHub(什么是DagsHub?) (英语).
Gotit.pub(什么是GotitPub?) 互联网电影数据库(IMDb)上"GotitPub"?
Hugging Face(什么是Huggingface?
科学卡斯特(科学卡斯特是什么？
演示文稿
建议和搜索工具
影响花(什么是影响花？)
CORE推荐人(CORE是什么？)
IArxiv 建议者
(IArxiv是什么东西？)
arXivLabs：与社区合作者的实验项目
arXivLabs是一个允许合作者在我们的网站上直接开发并分享新的arXiv特性的框架。
与arXivLabs合作的个人和组织都拥护并接受了我们的开放、社区、卓越和用户数据隐私的价值观。 arXiv致力于这些价值观，只与坚持这些价值观的伙伴合作。
有个能给ArXiv社区带来价值的项目吗？学习更多关于arXivLabs。
本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
Computer Science > Machine Learning
[Submitted on 28 May 2026 (v1), last revised 8 Sep 2026 (this version, v2)]
Title:The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer
View PDF HTML (experimental)
Abstract:This book provides a compact, derivation-oriented introduction to the mathematical foundations of modern generative artificial intelligence. Rather than surveying every recent architecture or implementation detail, it develops a coherent route through the ideas connecting major families of generative models, from PCA, probabilistic PCA, variational autoencoders, and diffusion models to normalising flows, autoregressive factorisations, GANs, Wasserstein GANs, and energy-based models. The aim is to make the structure of generative modelling more accessible without removing the mathematical substance needed to understand how these models are derived and related. The book is intended as a foundation-building primer for mathematically curious researchers, practitioners, and students.
Submission history
From: Tianhua Chen [view email]
[v1] Thu, 28 May 2026 10:12:00 UTC (125 KB)
[v2] Tue, 8 Sep 2026 07:17:36 UTC (1,168 KB)
Additional Features
References & Citations
Loading...
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender
(What is IArxiv?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Auto-fetched and translated by AI Atlas. All rights belong to the original author.