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Justyna P. Zwolak
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2017
S. S. Kalantre
,
Zwolak, J. P.
,
Ragole, S.
,
Wu, X.
,
Zimmerman, N. M.
,
Stewart, M. D.
, and
Taylor, J. M.
,
“
Machine Learning techniques for state recognition and auto-tuning in quantum dots
”
, 2017.
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2018
R. Dou
and
Zwolak, J. P.
,
“
Practitioner's guide to social network analysis: Examining physics anxiety in an active-learning setting
”
, 2018.
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C. A. Hass
,
Genz, F.
,
Kustusch, M. Bridget
,
Ouime, P. - P. A.
,
Pomian, K.
,
Sayre, E. C.
, and
Zwolak, J. P.
,
“
Studying community development: a network analytical approach
”
, 2018.
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J. P. Zwolak
,
Kalantre, S. S.
,
Wu, X.
,
Ragole, S.
, and
Taylor, J. M.
,
“
QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments
”
,
PLOS ONE
, vol. 13, no. 10, p. e0205844, 2018.
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2020
J. P. Zwolak
,
Kalantre, S. S.
,
McJunkin, T.
,
Weber, B. J.
, and
Taylor, J. M.
,
“
Ray-based classification framework for high-dimensional data
”
, 2020.
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J. P. Zwolak
,
McJunkin, T.
,
Kalantre, S. S.
,
Dodson, J. P.
,
MacQuarrie, E. R.
,
Savage, D. E.
,
Lagally, M. G.
,
Coppersmith, S. N.
,
Eriksson, M. A.
, and
Taylor, J. M.
,
“
Auto-tuning of double dot devices in situ with machine learning
”
,
Phys. Rev. Applied
, vol. 13, no. 034075 , 2020.
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2021
S. Guo
,
Fritsch, A. R.
,
Greenberg, C.
,
Spielman, I. B.
, and
Zwolak, J. P.
,
“
Machine-learning enhanced dark soliton detection in Bose-Einstein condensates
”
, 2021.
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