adaptive
A Python library for parallel active learning of mathematical functions, intelligently sampling parameter spaces to minimize evaluations.
What is adaptive?
Adaptive is a Python library for parallel active learning of mathematical functions. It intelligently samples parameter spaces by selecting the most informative points, reducing the number of function evaluations needed for accurate approximation or optimization. It is designed for computationally expensive functions where each evaluation takes significant time.
Researchers, scientists, and engineers working with expensive-to-evaluate mathematical functions, such as those in physics simulations, engineering design, or numerical analysis, who need efficient parameter space exploration.
Developers choose Adaptive for its combination of adaptive sampling algorithms, parallel execution capabilities, and live visualization, which together provide an efficient and interactive workflow for exploring complex functions with minimal code.
Overview
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
Use Cases
Best For
- Efficiently approximating expensive 1D or 2D functions with adaptive sampling
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