refactor(officefile): 按 md/latex/word 三层结构重组文档目录

将 Markdown 源文件移入 md/，LaTeX 工作目录保留在 latex/， Word 导出移入 word/；删除临时脚本、调试截图和空 stub。 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-29 14:25:21 +08:00
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+# 附录7：参考文献
+
+本部分整理教材中引用的论文、书籍和在线资源。
+
+论文
+
+# 基础理论
+
+4.  Universal Approximation Theorem (1989)
+
+    Scaling Laws for Neural Language Models (2020)
+
+# 计算机视觉
+
+6.  AlexNet (2012) - ImageNet Classification with Deep Convolutional Neural Networks
+
+    ResNet (2015) - Deep Residual Learning for Image Recognition
+
+    YOLO (2016) - You Only Look Once: Unified, Real-Time Object Detection
+
+    U-Net (2015) - Convolutional Networks for Biomedical Image Segmentation
+
+# Transformer与大模型
+
+10. Attention Is All You Need (2017)
+
+    BERT: Pre-training of Deep Bidirectional Transformers (2018)
+
+    GPT-3: Language Models are Few-Shot Learners (2020)
+
+    Training Language Models to Follow Instructions with Human Feedback (2022)
+
+# 生成式AI
+
+14. Denoising Diffusion Probabilistic Models (2020)
+
+    High-Resolution Image Synthesis with Latent Diffusion Models (2022)
+
+    ControlNet (2023)
+
+# AI Agent
+
+1.  LLM Powered Autonomous Agents (2023)
+
+2.  ReAct: Synergizing Reasoning and Acting in Language Models (2022)
+
+3.  
+
+# 书籍
+
+5.  深度学习
+
+6.  Deep Learning (Ian Goodfellow et al.)
+
+7.  Neural Networks and Deep Learning (Michael Nielsen)
+
+8.  强化学习
+
+9.  Reinforcement Learning: An Introduction (Sutton & Barto)
+
+10. 
+
+# 在线资源
+
+12. 课程
+
+13. CS231n: Convolutional Neural Networks for Visual Recognition
+
+14. Fast.ai Practical Deep Learning for Coders
+
+## 工具文档
+
+16. PyTorch: https://pytorch.org/docs/
+
+17. Ultralytics YOLO: https://docs.ultralytics.com/
+
+18. LangChain: https://python.langchain.com/
+
+## 博客
+
+20. Lil'Log (Lilian Weng): https://lilianweng.github.io/
+
+21. The Illustrated Transformer: https://jalammar.github.io/illustrated-transformer/
+
+22. 
+
+# 设计AI相关
+
+## 学术期刊
+
+25. Landscape and Urban Planning
+
+26. Environment and Planning B: Urban Analytics and City Science
+
+27. Automation in Construction
+
+## 会议
+
+29. CAAD Futures
+
+30. ACADIA
+
+31. eCAADe
+
+32. 
+
+# 数据集
+
+## 计算机视觉
+
+35. ImageNet
+
+36. COCO (Common Objects in Context)
+
+37. MNIST
+
+## 空间数据
+
+39. OpenStreetMap
+
+40. 路网数据、POI数据等
+
+# 许可说明
+
+部分内容引用自公开资源，遵循相应许可协议使用。
+
+**最后更新**：2026年4月