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louisfb01/best_AI_papers_2022
A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.
3.2k 199 +0/wk
GitHub
2022 ai artificial-intelligence computer-science computer-vision deep-learning innovation machine-learning machinelearning neural-network paper papers
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Star & Fork Trend (49 data points)
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louisfb01/best_AI_papers_2022 has +0 stars this period . 7-day velocity: -0.1%.
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| Metric | best_AI_papers_2022 | deep-learning-papers | Data-science-best-resources | eiten |
|---|---|---|---|---|
| Stars | 3.2k | 3.2k | 3.2k | 3.2k |
| Forks | 199 | 408 | 1.0k | 371 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | N/A | N/A | N/A | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | N/A | MIT | GPL-3.0 |
Capability Radar vs deep-learning-papers
best_AI_papers_2022
deep-learning-papers
Maintenance Activity 0
Last code push 904 days ago.
Community Engagement 31
Fork-to-star ratio: 6.2%. Lower fork ratio may indicate passive usage.
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.