BAMresearch/SequentialLearningApp
Sequential Learning App for Materials Discovery (SLAMD)
This tool helps materials scientists and researchers evaluate how well different AI algorithms can accelerate materials discovery using 'Sequential Learning'. You input existing materials datasets, and it outputs performance comparisons, showing how efficiently various algorithms identify promising new materials compared to random sampling. It's designed for researchers aiming to optimize experimental procedures and find novel materials with fewer, more targeted experiments.
No commits in the last 6 months.
Use this if you are a materials researcher or scientist with existing experimental datasets and want to benchmark Sequential Learning algorithms to find optimal material compositions more efficiently.
Not ideal if you are looking for a general-purpose machine learning library or if your primary goal is not accelerating materials discovery through sequential experimentation.
Stars
9
Forks
6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 27, 2023
Commits (30d)
0
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