yfzhang114/Generalization-Causality

• highreadme#1

  Reposition README's opening to clarify its nature as a research resource

  原因：

  当前

  This is a repository for organizing articles related to Domain generalization, OOD, optimization, data-centric learning, prompt learning, robutness, and causality. Most papers are linked to **my reading notes**.

  复制粘贴的修复

  复制

  This repository serves as a curated collection of my personal reading notes and organized articles on key research topics including Domain Generalization, Out-of-Distribution (OOD) learning, Causality, Robustness, Prompt Learning, Optimization, and Generative Models. It is designed as a resource for researchers to explore and understand the latest advancements in these fields, with most papers linked to detailed notes.

  待办完成忽略
• highabout#2

  Add a homepage URL to the repository's 'About' section

  原因：

  复制粘贴的修复

  复制

  https://yfzhang114.github.io/

  待办完成忽略
• mediumtopics#3

  Refine topics to include 'literature-review' and 'research-notes'

  原因：

  当前

  adaptation, causality, deep-learning, generative-model, machine-learning, optimization, robustness

  复制粘贴的修复

  复制

  adaptation, causality, deep-learning, generative-model, machine-learning, optimization, robustness, literature-review, research-notes, survey

  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 to improve deep learning model performance when data distribution shifts between training and testing?

  你：未被推荐
  AI 推荐顺序：

  1. ADDA
  2. DANN
  3. CDAN
  4. PyTorch
  5. TensorFlow
  6. Keras
  7. ImageNet
  8. BERT
  9. RoBERTa
  10. Hugging Face Transformers
  11. GPT
  12. Albumentations
  13. imgaug
  14. Keras ImageDataGenerator
  15. CutMix
  16. Mixup
  17. Augly (Facebook AI)
  18. Scikit-learn
  19. VotingClassifier
  20. StackingClassifier
  21. StackingRegressor
  22. Foolbox
  23. Advertorch
  24. Group DRO
  25. FixMatch
  26. UDA
  27. Mean Teacher
  28. Pandas
  29. Canny
  30. GLCM
  31. librosa
  32. OpenCV

  AI 推荐了 32 个替代方案，却始终没点名 yfzhang114/Generalization-Causality。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Seeking resources to understand causality and robustness for out-of-distribution machine learning models.

  你：未被推荐
  AI 推荐顺序：

  1. Elements of Causal Inference: Foundations and Learning Algorithms
  2. Causal Inference in Statistics: A Primer
  3. Invariant Risk Minimization (IRM)
  4. Domain-Adversarial Training of Neural Networks (DANN)
  5. Distributionally Robust Optimization (DRO)
  6. PC algorithm
  7. FCI algorithm
  8. Causal-learn (cai-lab/Causal-learn)
  9. NeurIPS Workshop on Causal Inference and Machine Learning
  10. ICML Workshop on Causality in Machine Learning

  AI 推荐了 10 个替代方案，却始终没点名 yfzhang114/Generalization-Causality。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 yfzhang114/Generalization-Causality?

  pass
  ⚠AI 未点名 yfzhang114/Generalization-Causality —— 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 yfzhang114/Generalization-Causality in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 yfzhang114/Generalization-Causality

  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 yfzhang114/Generalization-Causality solve, and who is the primary audience?

  pass
  ⚠AI 未点名 yfzhang114/Generalization-Causality —— 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？