178 citations · 976 across the 49 of their papers we have counts for
3 papers · 1 filter
Benchmarking machine learning models for multi-class state recognition in double quantum dot data
Valeria Díaz Moreno, Ryan P Khalili, Daniel Schug +2
Semiconductor quantum dots (QDs) are a leading platform for scalable quantum processors. However, scaling to large arrays requires reliable, automated tuning strategies for devices…
Automation of Quantum Dot Measurement Analysis via Explainable Machine Learning
Daniel Schug, Tyler J. Kovach, M. A. Wolfe +6
The rapid development of quantum dot (QD) devices for quantum computing has necessitated more efficient and automated methods for device characterization and tuning. This work demo…
Extending Explainable Boosting Machines to Scientific Image Data
Daniel Schug, Sai Yerramreddy, Rich Caruana +2
As the deployment of computer vision technology becomes increasingly common in science, the need for explanations of the system and its output has become a focus of great concern.…