Eliska Greplova
Cited by
Cited by
Correlation functions and conditioned quantum dynamics in photodetection theory
Q Xu, E Greplova, B Julsgaard, K Mølmer
Physica Scripta 90 (12), 128004, 2015
Hamiltonian learning for quantum error correction
A Valenti, E van Nieuwenburg, S Huber, E Greplova
Physical Review Research 1 (3), 033092, 2019
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
Quantum information with fermionic Gaussian states
E Greplova
LMU München, 2013
Quantum parameter estimation with a neural network
E Greplova, CK Andersen, K Mølmer
arXiv preprint arXiv:1711.05238, 2017
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
Quantum teleportation with continuous measurements
E Greplova, K Mølmer, CK Andersen
Physical Review A 94 (4), 042334, 2016
Degradability of fermionic gaussian channels
E Greplová, G Giedke
Physical review letters 121 (20), 200501, 2018
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
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
Learning Algorithms for Control and Characterization of Quantum Matter
E Greplova, G Jin, A Valenti, J Bucko, I Romero, F Schäfer, S Huber
Bulletin of the American Physical Society, 2021
Customizable neural-network states for topological phases
A Valenti, E Greplova, N Lindner, S Huber
Bulletin of the American Physical Society, 2021
Correlation-Enhanced Neural Networks as Interpretable Variational Quantum States
A Valenti, E Greplova, NH Lindner, SD Huber
arXiv preprint arXiv:2103.05017, 2021
Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics
A Valenti, G Jin, J Léonard, SD Huber, E Greplova
arXiv preprint arXiv:2103.01240, 2021
Introduction to Machine Learning for the Sciences
T Neupert, MH Fischer, E Greplova, K Choo, M Denner
arXiv preprint arXiv:2102.04883, 2021
Solving optimization tasks in condensed matter
E Greplova
Nature Machine Intelligence 2 (10), 557-558, 2020
Let’s take this discussion online
A Akhmerov, X Bonet-Monroig, V Fatemi, E Greplova, ...
Europhysics News 51 (3), 20-212, 2020
Topological codes revisited: Hamiltonian learning and topological phase transitions
E Greplova, A Valenti, E Van Nieuwenburg, G Boschung, F Schäfer, ...
Bulletin of the American Physical Society 65, 2020
Maschinelles Lernen ohne neuronale Netzwerke
K Choo, E Greplova, MH Fischer, T Neupert
Machine Learning kompakt, 7-24, 2020
Unüberwachtes Lernen
K Choo, E Greplova, MH Fischer, T Neupert
Machine Learning kompakt, 47-58, 2020
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