7 citations · 14 across the 3 of their papers we have counts for
3 papers
cond-mat.mes-hall2024★ 1 cited
Machine Learning-Based Reward-Driven Tuning of Scanning Probe Microscopy: Towards Fully Automated Microscopy
Yu Liu, Roger Proksch, Jason Bemis +8
Since the dawn of scanning probe microscopy (SPM), tapping or intermittent contact mode has been one of the most widely used imaging modes. Manual optimization of tapping mode not…
cond-mat.mtrl-sci2024★ 7 cited
Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation
Yu Liu, Utkarsh Pratiush, Jason Bemis +8
The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key ele…
cs.LG2023★ 6 cited
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments
Arpan Biswas, Yongtao Liu, Nicole Creange +6
Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements…