js05212/BayesianDeepLearning-Survey

• highreadme#1

  Clarify README's opening to emphasize 'survey/resource list' nature

  原因：

  当前

  This is an updating survey for Bayesian Deep Learning (BDL), an constantly updated and extended version for the manuscript, 'A Survey on Bayesian Deep Learning', published in **ACM Computing Surveys** 2020.

  复制粘贴的修复

  复制

  This repository provides an actively updated and extended survey of Bayesian Deep Learning (BDL), serving as a comprehensive resource and curated collection of papers. It is the online companion to 'A Survey on Bayesian Deep Learning', published in **ACM Computing Surveys** 2020.

  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, specifying the chosen open-source license (e.g., MIT, Apache-2.0, CC-BY-4.0 for content).

  待办完成忽略
• mediumhomepage#3

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

  原因：

  复制粘贴的修复

  复制

  Add `http://wanghao.in/BDL.html` as the homepage URL 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

  What are the latest advancements and applications in probabilistic deep learning for various fields?

  你：未被推荐
  AI 推荐顺序：

  1. Pyro
  2. TensorFlow Probability
  3. Stan
  4. PyMC
  5. Google's DeepMind
  6. Google Health
  7. $eta$-VAE
  8. Conditional VAEs (CVAEs)
  9. Real NVP (NICE)
  10. Glow
  11. DALL-E 2
  12. Stable Diffusion
  13. Google's AudioLM
  14. Probabilistic Policy Optimization (PPO)
  15. Soft Actor-Critic (SAC)
  16. Deep Bayesian Q-Networks (DBQN)
  17. DeepAR (Amazon)
  18. Edward2

  AI 推荐了 18 个替代方案，却始终没点名 js05212/BayesianDeepLearning-Survey。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Looking for a comprehensive overview of uncertainty quantification methods in deep learning models.

  你：未被推荐
  AI 推荐顺序：

  1. Uncertainty in Deep Learning
  2. Deep Learning with Python
  3. TensorFlow (tensorflow/tensorflow)
  4. Keras (keras-team/keras)
  5. A Survey of Uncertainty in Deep Neural Networks
  6. Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
  7. Google AI
  8. Microsoft Research
  9. Medium
  10. Towards Data Science
  11. PyTorch (pytorch/pytorch)
  12. Probabilistic Machine Learning: An Introduction
  13. Awesome Uncertainty in Deep Learning (yandex-research/awesome-uncertainty-in-deep-learning)

  AI 推荐了 13 个替代方案，却始终没点名 js05212/BayesianDeepLearning-Survey。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 js05212/BayesianDeepLearning-Survey?

  pass
  ⚠AI 未点名 js05212/BayesianDeepLearning-Survey —— 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 js05212/BayesianDeepLearning-Survey in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 js05212/BayesianDeepLearning-Survey

  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 js05212/BayesianDeepLearning-Survey solve, and who is the primary audience?

  pass
  ⚠AI 未点名 js05212/BayesianDeepLearning-Survey —— 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？