feat: 完整中文翻译 maths-cs-ai-compendium（数学·计算机科学·AI 知识大全）

翻译自英文原版 maths-cs-ai-compendium，共 20 章全部完成。第01章向量 | 第02章矩阵 | 第03章微积分第04章统计学 | 第05章概率论 | 第06章机器学习第07章计算语言学 | 第08章计算机视觉 | 第09章音频与语音第10章多模态学习 | 第11章自主系统 | 第12章图神经网络第13章计算与操作系统 | 第14章数据结构与算法第15章生产级软件工程 | 第16章 SIMD与GPU编程第17章 AI推理 | 第18章 ML系统设计第19章应用人工智能 | 第20章前沿人工智能翻译说明： - 所有数学公式 $...$ / $$...$$、代码块、图片引用完整保留 - mkdocs.yml 配置中文导航 + language: zh - README.md 已翻译为中文（兼 docs/index.md） - docs/ 目录包含指向各章文件的 symlink - 约 29,000 行中文内容，排除 .cache/ 构建缓存
2026-05-03 10:23:20 +08:00
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+  <text x="350" y="22" fill="#333" font-size="14" font-weight="bold" text-anchor="middle">Diffusion: Forward and Reverse Processes</text>
+
+  <!-- Forward process (top row) -->
+  <text x="350" y="48" fill="#e74c3c" font-size="11" font-weight="bold" text-anchor="middle">Forward Process: Gradually Add Noise (q)</text>
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+  <text x="295" y="145" fill="#333" font-size="10" text-anchor="middle">x_t</text>
+
+  <!-- Dots (ellipsis) -->
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+  <circle cx="480" cy="115" r="3" fill="#888"/>
+  <text x="460" y="145" fill="#333" font-size="10" text-anchor="middle">x_{T-1}</text>
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+  <text x="575" y="145" fill="#333" font-size="10" text-anchor="middle" font-weight="bold">x_T</text>
+  <text x="575" y="157" fill="#666" font-size="8" text-anchor="middle">≈ N(0,I)</text>
+
+  <!-- Reverse process (bottom) -->
+  <text x="350" y="185" fill="#27ae60" font-size="11" font-weight="bold" text-anchor="middle">Reverse Process: Learn to Denoise (p_θ)</text>
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+  <text x="350" y="205" fill="#666" font-size="14" text-anchor="middle">···</text>
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+  <text x="120" y="215" fill="#27ae60" font-size="7" text-anchor="middle">−ε_θ</text>
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+  <text x="350" y="242" fill="#333" font-size="9" text-anchor="middle">Neural network ε_θ(x_t, t) predicts the noise added at each step.</text>
+  <text x="350" y="256" fill="#666" font-size="9" text-anchor="middle">Training loss: L = E[ ‖ε − ε_θ(x_t, t)‖² ]. Simple MSE on noise prediction.</text>
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