Active Learning Pipeline For Optimal Ranking Estimation
Project description
ALPineFOREst
Active Learning Pipeline For Optimal Ranking Estimation
ALPineFOREst is a flexible, modular framework for conducting large-scale active learning campaigns in scientific and materials research. It supports molecular dynamics (MD)-based evaluations, customizable models (e.g., Gaussian Processes), and popular Bayesian optimization strategies like Thompson Sampling — all within a high-throughput, reproducible pipeline.
Installation
Install via PyPI:
pip install alpfore
Or to install from source:
git clone https://github.com/nherringer/ALPineFOREst.git
cd ALPineFOREst
pip install -e .
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