
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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
