AL
mir-group/allegro
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
472 72 +0/wk
GitHub
atomistic-simulations computational-chemistry deep-learning drug-discovery force-fields interatomic-potentials machine-learning materials-science molecular-dynamics pytorch
Trend
0
Star & Fork Trend (17 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
mir-group/allegro has +0 stars this period . Velocity data will be available after more historical data is collected.
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Signal-backed technical analysis will be available soon.
| Metric | allegro | synthesizing | torchmd-net | Coursera-Deep-Learning |
|---|---|---|---|---|
| Stars | 472 | 472 | 472 | 472 |
| Forks | 72 | 86 | 97 | 363 |
| Weekly Growth | +0 | +0 | +1 | +0 |
| Language | Python | Python | Python | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | MIT | MIT |
Capability Radar vs synthesizing
allegro
synthesizing
Maintenance Activity 83
Last code push 36 days ago.
Community Engagement 76
Fork-to-star ratio: 15.3%. 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.