Search Results for author: Kyle Kelley

Found 3 papers, 2 papers with code

Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning

no code implementations30 May 2022 Maxim Ziatdinov, Yongtao Liu, Kyle Kelley, Rama Vasudevan, Sergei V. Kalinin

Recent progress in machine learning methods, and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs), have propelled automated and autonomous microscopies to the forefront of attention of the scientific community.

Active Learning Bayesian Inference +3

Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy

1 code implementation20 Apr 2021 Yongtao Liu, Rama K. Vasudevan, Kyle Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim Ziatdinov

A shift-invariant variational autoencoder (shift-VAE) is developed as an unsupervised method for the analysis of spectral data in the presence of shifts along the parameter axis, disentangling the physically-relevant shifts from other latent variables.

Denoising Dimensionality Reduction

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics

1 code implementation25 Nov 2020 Rama K. Vasudevan, Kyle Kelley, Hiroshi Funakubo, Stephen Jesse, Sergei V. Kalinin, Maxim Ziatdinov

Polarization dynamics in ferroelectric materials are explored via the automated experiment in Piezoresponse Force Spectroscopy.

Disordered Systems and Neural Networks Data Analysis, Statistics and Probability

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