most citedHypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries

75 citations · 80 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.dis-nn2022★ 1 cited

Learning and predicting photonic responses of plasmonic nanoparticle assemblies via dual variational autoencoders

Muammer Y. Yaman, Sergei V. Kalinin, Kathryn N. Guye +2

We demonstrate the application of machine learning for rapid and accurate extraction of plasmonic particles cluster geometries from hyperspectral image data via a dual variational…

cond-mat.dis-nn2022★ 1 cited

Probing electron beam induced transformations on a single defect level via automated scanning transmission electron microscopy

Kevin M. Roccapriore, Matthew G. Boebinger, Ondrej Dyck +4

The robust approach for real-time analysis of the scanning transmission electron microscopy (STEM) data streams, based on the ensemble learning and iterative training (ELIT) of dee…

cs.LG2022★ 2 cited

Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach

Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov +1

Unsupervised and semi-supervised ML methods such as variational autoencoders (VAE) have become widely adopted across multiple areas of physics, chemistry, and materials sciences du…

cond-mat.mtrl-sci2022

Automated Experiments of Local Non-linear Behavior in Ferroelectric Materials

Yongtao Liu, Kyle P. Kelley, Rama K. Vasudevan +7

We develop and implement an automated experiment in multimodal imaging to probe structural, chemical, and functional behaviors in complex materials and elucidate the dominant physi…

cond-mat.mtrl-sci2021★ 75 cited

Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries

Maxim Ziatdinov, Yongtao Liu, Anna N. Morozovska +4

Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and elect…

cond-mat.mtrl-sci2021★ 1 cited

Automated experiment in 4D-STEM: exploring emergent physics and structural behaviors

Kevin M. Roccapriore, Ondrej Dyck, Mark P. Oxley +2

Automated experiments in 4D Scanning Transmission Electron Microscopy are implemented for rapid discovery of local structures, symmetry-breaking distortions, and internal electric…