NB
philipperemy/n-beats
Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.
901 169 +0/wk
GitHub
deep-learning neural-networks pytorch series-forecasting
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0
Star & Fork Trend (17 data points)
Stars
Forks
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philipperemy/n-beats has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | n-beats | similarities | DSINE | retinanet-examples |
|---|---|---|---|---|
| Stars | 901 | 900 | 899 | 899 |
| Forks | 169 | 88 | 43 | 265 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Jupyter Notebook | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | Apache-2.0 | NOASSERTION | BSD-3-Clause |
Capability Radar vs similarities
n-beats
similarities
Maintenance Activity 0
Last code push 1133 days ago.
Community Engagement 94
Fork-to-star ratio: 18.8%. 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.