bgavran/Category_Theory_Machine_Learning

• highreadme#1

  Clarify README's opening sentence to emphasize "curated list of papers"

  原因：

  当前

  This repository aims to list all of the relevant papers, grouped by fields.

  复制粘贴的修复

  复制

  This repository is a curated list of academic papers studying machine learning through the lens of category theory, grouped by fields.

  待办完成忽略
• highlicense#2

  Add a LICENSE file to the repository

  原因：

  复制粘贴的修复

  复制

  Create a `LICENSE` file in the repository root with a suitable open-source license, such as CC-BY-4.0 for content.

  待办完成忽略
• mediumhomepage#3

  Add a homepage URL to the repository settings

  原因：

  复制粘贴的修复

  复制

  Add a relevant URL (e.g., a project page, personal website, or related resource) to the "Homepage" field in the repository settings.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How can category theory be applied to understand and improve machine learning models?

  你：未被推荐
  AI 推荐顺序：

  1. Functorial Machine Learning (FML)
  2. Monoidal Categories
  3. Topos Theory
  4. Lenses
  5. Haskell's `lens` package
  6. Categorical Deep Learning
  7. Applied Category Theory for Machine Learning
  8. Probabilistic Monads
  9. Haskell
  10. TensorFlow
  11. PyTorch

  AI 推荐了 11 个替代方案，却始终没点名 bgavran/Category_Theory_Machine_Learning。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Where can I find academic papers on category theory applications in deep learning architectures?

  你：未被推荐
  AI 推荐顺序：

  1. arXiv.org
  2. Google Scholar
  3. Semantic Scholar
  4. MathOverflow
  5. Cross Validated
  6. NeurIPS
  7. ICML
  8. ICLR
  9. AISTATS
  10. JMLR
  11. TNNLS
  12. PNAS
  13. Nature Machine Intelligence
  14. Applied Category Theory (ACT) Conference

  AI 推荐了 14 个替代方案，却始终没点名 bgavran/Category_Theory_Machine_Learning。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of bgavran/Category_Theory_Machine_Learning?

  pass
  ⚠AI 未点名 bgavran/Category_Theory_Machine_Learning —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts bgavran/Category_Theory_Machine_Learning in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 bgavran/Category_Theory_Machine_Learning

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo bgavran/Category_Theory_Machine_Learning solve, and who is the primary audience?

  pass
  ⚠AI 未点名 bgavran/Category_Theory_Machine_Learning —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？