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A Natural Basis for Unsupervised Machine Learning on Scanning Diffraction Data

Published online by Cambridge University Press:  01 August 2018

Paul Cueva ,
Elliot Padget  and
David A. Muller
Paul Cueva
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA
Elliot Padget
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA
David A. Muller
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA Kavli Institute at Cornell for Nanoscale Science, Ithaca, NY, USA

Abstract

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Abstract
Information
Microscopy and Microanalysis , Volume 24 , Supplement S1: Proceedings of Microscopy & Microanalysis 2018 , August 2018 , pp. 490 - 491
Copyright
© Microscopy Society of America 2018 

References

[1] Tate, M, et al., Microscopy and Microanalysis 22 2016) pp. 237–249.Google Scholar
[2] Belianinov, A, et al., Advanced Structural and Chemical Imaging 1(1 2015) p. 6.Google Scholar
[3] Xu, W LeBeau, J Microscopy and Microanalysis 23(S1 2017) pp: 120–121.Google Scholar
[4] PC was supported by the Center for Bright Beams, an NSF STC (PHY-1549132). This work made use of the Cornell Center for Materials Research Shared Facilities, an NSF MRSEC (DMR-1719875 and NSF-MRI-1429155). EP supported by an NSF Graduate Research Fellowship (DGE-1650441).Google Scholar