Published January 2, 2025
| Version v1
Dataset
Open
Figure data files for paper "Automation of quantum dot measurement analysis via explainable machine learning"
Authors/Creators
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1.
University of Maryland
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2.
University of Wisconsin-Madison
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3.
National Institute of Standards and Technology
Description
This dataset contains all source files for the figures in the paper titled "Automation of quantum dot measurement analysis via explainable machine learning" published in Machine Learning: Science and Technology. In this paper, we propose and demonstrate a data vectorization method that involves mathematical modeling to mimic the experimental data. We then show that this new method offers superior explainability of model prediction without sacrificing accuracy.
The experimental data used in this work is included in the QFlow Triangles: Quantum dot triangle plots data for machine learning dataset.
Files
README.md
Files
(7.5 MB)
| Name | Size | Download all |
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md5:c546791beb46361a93f4859019b486dd
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5.4 MB | Preview Download |
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md5:d266e860581161fd7e61ddd4f9ad132e
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464.2 kB | Preview Download |
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md5:c48bd8b172ad1bb3e7dad16e3d6cc256
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495.1 kB | Preview Download |
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md5:2ea02d4b4c4f2d9bec69cbbeb4bfbe39
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722.2 kB | Preview Download |
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md5:09bd9deae6b25ca0f085cb49fbeb5917
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468.0 kB | Preview Download |
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md5:f9fc462b830568228d597b6c55277060
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3.8 kB | Preview Download |
Additional details
Related works
- Is published in
- Publication: arXiv:2402.13699 (arXiv)
Dates
- Accepted
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2024-12-17
Software
- Programming language
- Python