SimonBlanke/Gradient-Free-Optimizers

Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces

1.3k 95 +0/wk

GitHub

bayesian-optimization blackbox-optimization constrained-optimization evolution-strategies gradient-free-optimization hill-climbing hyperparameter-optimization machine-learning meta-heuristic nelder-mead optimization particle-swarm-optimization

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Star & Fork Trend (10 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 1.3k

forks 95

Growth Velocity

SimonBlanke/Gradient-Free-Optimizers 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	Gradient-Free-Optimizers	ktrain	Forge	gnes
Stars	1.3k	1.3k	1.3k	1.3k
Forks	95	260	172	210
Weekly Growth	+0	+0	+0	+0
Language	Python	Jupyter Notebook	Swift	Python
Sources	1	1	1	1
License	MIT	Apache-2.0	MIT	NOASSERTION

Capability Radar vs ktrain

Gradient-Free-Optimizers

ktrain

Maintenance Activity 100

Last code push 3 days ago.

Community Engagement 38

Fork-to-star ratio: 7.5%. Lower fork ratio may indicate passive usage.

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.