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SciML/SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
2.0k 368 +0/wk
GitHub
differential-equations gpu-computing lecture-notes neural-networks neural-ode neural-sde numerical-methods parallelism performance-engineering scientific-machine-learning scientific-simulators sciml
Trend
0
Star & Fork Trend (17 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
SciML/SciMLBook has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | SciMLBook | ViZDoom | ViTPose | diamond |
|---|---|---|---|---|
| Stars | 2.0k | 2.0k | 2.0k | 2.0k |
| Forks | 368 | 440 | 247 | 149 |
| Weekly Growth | +0 | +1 | +5 | +0 |
| Language | HTML | C++ | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | N/A | N/A | Apache-2.0 | MIT |
Capability Radar vs ViZDoom
SciMLBook
ViZDoom
Maintenance Activity 87
Last code push 30 days ago.
Community Engagement 92
Fork-to-star ratio: 18.4%. 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 30
No clear license detected — proceed with caution.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.