CL
GMvandeVen/continual-learning
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
1.8k 344 +0/wk
GitHub
artificial-neural-networks class-incremental-learning continual-learning deep-learning distillation domain-incremental-learning elastic-weight-consolidation generative-models gradient-episodic-memory icarl incremental-learning lifelong-learning
Trend
3
Star & Fork Trend (21 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
GMvandeVen/continual-learning has +0 stars this period . 7-day velocity: 0.1%.
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| Metric | continual-learning | Code-LMs | Machine-Learning-Flappy-Bird | PhiFlow |
|---|---|---|---|---|
| Stars | 1.8k | 1.8k | 1.8k | 1.8k |
| Forks | 344 | 264 | 392 | 226 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Jupyter Notebook | Python | JavaScript | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | MIT | MIT |
Capability Radar vs Code-LMs
continual-learning
Code-LMs
Maintenance Activity 15
Last code push 154 days ago.
Community Engagement 93
Fork-to-star ratio: 18.7%. 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.