AGENT SKILL
bayesian-deep-learning
Bayesian neural networks, uncertainty in deep learning, and probabilistic DL
- License 许可
- MIT
- 所属仓库
- NeuralBlitz/Mito
- 最近更新
- 2026-04-21
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- bayesian-deep-learning
- license
- MIT
- metadata
- { "audience": "researchers", "category": "machine-learning" }
- description
- Bayesian neural networks, uncertainty in deep learning, and probabilistic DL
- compatibility
- opencode
03 SKILL.md 正文
What I do
- Build Bayesian neural networks
- Quantify uncertainty in DL
- Apply variational inference
- Use Monte Carlo dropout
When to use me
When working on uncertainty quantification in deep learning.
Key Concepts
- Bayesian NNs
- Variational inference
- Dropout as Bayesian
- Weight uncertainty
- Epistemic uncertainty
- Aleatoric uncertainty
- Model calibration
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