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Eliska Greplova
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Unsupervised identification of topological phase transitions using predictive models
E Greplova, A Valenti, G Boschung, F Schäfer, N Lörch, SD Huber
New Journal of Physics 22 (4), 045003, 2020
792020
Hamiltonian learning for quantum error correction
A Valenti, E van Nieuwenburg, S Huber, E Greplova
Physical Review Research 1 (3), 033092, 2019
722019
Automated tuning of double quantum dots into specific charge states using neural networks
R Durrer, B Kratochwil, JV Koski, AJ Landig, C Reichl, W Wegscheider, ...
Physical Review Applied 13 (5), 054019, 2020
492020
Modern applications of machine learning in quantum sciences
A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ...
arXiv preprint arXiv:2204.04198, 2022
462022
Correlation functions and conditioned quantum dynamics in photodetection theory
Q Xu, E Greplova, B Julsgaard, K Mølmer
Physica Scripta 90 (12), 128004, 2015
362015
Fully automated identification of two-dimensional material samples
E Greplova, C Gold, B Kratochwil, T Davatz, R Pisoni, A Kurzmann, ...
Physical Review Applied 13 (6), 064017, 2020
242020
Quantum parameter estimation with a neural network
E Greplova, CK Andersen, K Mølmer
arXiv preprint arXiv:1711.05238, 2017
242017
Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics
A Valenti, G Jin, J Léonard, SD Huber, E Greplova
Physical Review A 105 (2), 023302, 2022
232022
Machine learning kompakt
K Choo, E Greplova, MH Fischer, T Neupert, T Neupert, M Fischer
Springer Fachmedien Wiesbaden. https://doi. org/10.1007/978-3-658-32268-7, 2020
212020
Correlation-enhanced neural networks as interpretable variational quantum states
A Valenti, E Greplova, NH Lindner, SD Huber
Physical Review Research 4 (1), L012010, 2022
202022
Quantum information with fermionic Gaussian states
E Greplova
LMU München, 2013
172013
Quantum teleportation with continuous measurements
E Greplova, K Mølmer, CK Andersen
Physical Review A 94 (4), 042334, 2016
142016
Introduction to machine learning for the sciences
T Neupert, MH Fischer, E Greplova, K Choo, MM Denner
arXiv preprint arXiv:2102.04883, 2021
102021
Untrained physically informed neural network for image reconstruction of magnetic field sources
AEE Dubois, DA Broadway, A Stark, MA Tschudin, AJ Healey, SD Huber, ...
Physical Review Applied 18 (6), 064076, 2022
92022
Degradability of fermionic gaussian channels
E Greplová, G Giedke
Physical Review Letters 121 (20), 200501, 2018
92018
Modern applications of machine learning in quantum sciences. 2022. doi: 10.48550
A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ...
arXiv preprint ARXIV.2204.04198, 0
9
Adversarial Hamiltonian learning of quantum dots in a minimal Kitaev chain
R Koch, D Van Driel, A Bordin, JL Lado, E Greplova
Physical Review Applied 20 (4), 044081, 2023
62023
Modern applications of machine learning in quantum sciences, arXiv e-prints
A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ...
arXiv preprint arXiv:2204.04198, 2022
62022
Conditioned spin and charge dynamics of a single-electron quantum dot
E Greplova, EA Laird, GAD Briggs, K Mølmer
Physical Review A 96 (5), 052104, 2017
62017
Modern applications of machine learning in quantum sciences (2022)
A Dawid, J Arnold, B Requena, A Gresch, M Płodzien, K Donatella, ...
arXiv preprint arXiv:2204.04198, 0
5
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