75 citations · 297 across the 47 of their papers we have counts for
7 papers · 1 filter
Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale
Ralph Bulanadi, Jefferey Baxter, Arpan Biswas +5
Self-driving laboratories or autonomous experimentation are emerging as transformative platforms for accelerating scientific discovery. Bayesian optimization (BO) is among the most…
Quality-Controlled Active Learning via Gaussian Processes for Robust Structure-Property Learning in Autonomous Microscopy
Jawad Chowdhury, Ganesh Narasimha, Jan-Chi Yang +2
Autonomous experimental systems are increasingly used in materials research to accelerate scientific discovery, but their performance is often limited by low-quality, noisy data. T…
Unraveling the Impact of Initial Choices and In-Loop Interventions on Learning Dynamics in Autonomous Scanning Probe Microscopy
Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo +1
The current focus in Autonomous Experimentation (AE) is on developing robust workflows to conduct the AE effectively. This entails the need for well-defined approaches to guide the…
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…
Physics and Chemistry from Parsimonious Representations: Image Analysis via Invariant Variational Autoencoders
Mani Valleti, Yongtao Liu, Sergei Kalinin
Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functiona…
Active learning in open experimental environments: selecting the right information channel(s) based on predictability in deep kernel learning
Maxim Ziatdinov, Yongtao Liu, Sergei V. Kalinin
Active learning methods are rapidly becoming the integral component of automated experiment workflows in imaging, materials synthesis, and computation. The distinctive aspect of ma…