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oneTaken/awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
765 125 +0/wk
GitHub
awesome awesome-list chainer computer-vision cvpr deep-learning eccv iccv iclr icml interpretability keras
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Star & Fork Trend (38 data points)
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| Metric | awesome_deep_learning_interpretability | awesome-emdl | awesome-photogrammetry | VLN-CE |
|---|---|---|---|---|
| Stars | 765 | 765 | 766 | 766 |
| Forks | 125 | 167 | 56 | 82 |
| Weekly Growth | +0 | +0 | +0 | +1 |
| Language | N/A | N/A | N/A | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | N/A | MIT |
Capability Radar vs awesome-emdl
awesome_deep_learning_interpretability
awesome-emdl
Maintenance Activity 0
Last code push 730 days ago.
Community Engagement 82
Fork-to-star ratio: 16.3%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.