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SimplexLab/TorchJD
Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning).
315 15 +1/wk
GitHub
deep-learning jacobian-descent multi-objective-optimization multi-task-learning multiobjective-optimization multitask-learning optimization python pytorch torch
Trend
3
Star & Fork Trend (15 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
SimplexLab/TorchJD has +1 stars this period . 7-day velocity: 1.9%.
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| Metric | TorchJD | naturalcc | zpy | physicsnemo-sym |
|---|---|---|---|---|
| Stars | 315 | 318 | 321 | 323 |
| Forks | 15 | 59 | 35 | 121 |
| Weekly Growth | +1 | +0 | +0 | +0 |
| Language | Python | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | GPL-3.0 | Apache-2.0 |
Capability Radar vs naturalcc
TorchJD
naturalcc
Maintenance Activity 100
Last code push 0 days ago.
Community Engagement 69
Fork-to-star ratio: 4.8%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 59
+1 stars this period — 0.32% growth rate.
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.