Reinforcement Learning for Quantum Control with Feedback:
Gespeichert in:
1. Verfasser: | |
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Format: | Abschlussarbeit Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Erlangen ; Nürnberg
Friedrich-Alexander-Universität Erlangen-Nürnberg
2023
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Schlagworte: | |
Online-Zugang: | kostenfrei kostenfrei kostenfrei |
Beschreibung: | 1 Online-Ressource Illustrationen, Diagramme |
Internformat
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spelling | Porotti, Riccardo (DE-588)1305392884 aut Reinforcement Learning for Quantum Control with Feedback vorgelegt von Riccardo Porotti Bestärkendes Lernen für Quanten Kontrolle mit Rückkopplung Erlangen ; Nürnberg Friedrich-Alexander-Universität Erlangen-Nürnberg 2023 1 Online-Ressource Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Dissertation Friedrich-Alexander-Universität Erlangen-Nürnberg 2023 Archivierung/Langzeitarchivierung gewährleistet DE-101 pdager 4\p Maschinelles Lernen (DE-588)4193754-5 gnd 5\p Neuronales Netz (DE-588)4226127-2 gnd 6\p Bestärkendes Lernen Künstliche Intelligenz (DE-588)4825546-4 gnd 7\p Lernendes System (DE-588)4120666-6 gnd 8\p Deep learning (DE-588)1135597375 gnd 9\p Soft Computing (DE-588)4455833-8 gnd reinforcement learning quantum control (DE-588)4113937-9 Hochschulschrift gnd-content https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-238948 Resolving-System kostenfrei Volltext https://d-nb.info/130469884X/34 Langzeitarchivierung Nationalbibliothek kostenfrei Volltext application/pdf https://open.fau.de/handle/openfau/23894 Verlag kostenfrei Volltext 1\p aepkn 0,99813 20231003 DE-101 https://d-nb.info/provenance/plan#aepkn 2\p emasg 0,55015 20231003 DE-101 https://d-nb.info/provenance/plan#emasg 3\p npi 20231002 DE-101 https://d-nb.info/provenance/plan#npi 4\p emagnd 0,48728 20231003 DE-101 https://d-nb.info/provenance/plan#emagnd 5\p emagnd 0,39276 20231003 DE-101 https://d-nb.info/provenance/plan#emagnd 6\p emagnd 0,17574 20231003 DE-101 https://d-nb.info/provenance/plan#emagnd 7\p emagnd 0,10704 20231003 DE-101 https://d-nb.info/provenance/plan#emagnd 8\p emagnd 0,07225 20231003 DE-101 https://d-nb.info/provenance/plan#emagnd 9\p emagnd 0,05624 20231003 DE-101 https://d-nb.info/provenance/plan#emagnd |
spellingShingle | Porotti, Riccardo Reinforcement Learning for Quantum Control with Feedback 4\p Maschinelles Lernen (DE-588)4193754-5 gnd 5\p Neuronales Netz (DE-588)4226127-2 gnd 6\p Bestärkendes Lernen Künstliche Intelligenz (DE-588)4825546-4 gnd 7\p Lernendes System (DE-588)4120666-6 gnd 8\p Deep learning (DE-588)1135597375 gnd 9\p Soft Computing (DE-588)4455833-8 gnd |
subject_GND | (DE-588)4193754-5 (DE-588)4226127-2 (DE-588)4825546-4 (DE-588)4120666-6 (DE-588)1135597375 (DE-588)4455833-8 (DE-588)4113937-9 |
title | Reinforcement Learning for Quantum Control with Feedback |
title_alt | Bestärkendes Lernen für Quanten Kontrolle mit Rückkopplung |
title_auth | Reinforcement Learning for Quantum Control with Feedback |
title_exact_search | Reinforcement Learning for Quantum Control with Feedback |
title_exact_search_txtP | Reinforcement Learning for Quantum Control with Feedback |
title_full | Reinforcement Learning for Quantum Control with Feedback vorgelegt von Riccardo Porotti |
title_fullStr | Reinforcement Learning for Quantum Control with Feedback vorgelegt von Riccardo Porotti |
title_full_unstemmed | Reinforcement Learning for Quantum Control with Feedback vorgelegt von Riccardo Porotti |
title_short | Reinforcement Learning for Quantum Control with Feedback |
title_sort | reinforcement learning for quantum control with feedback |
topic | 4\p Maschinelles Lernen (DE-588)4193754-5 gnd 5\p Neuronales Netz (DE-588)4226127-2 gnd 6\p Bestärkendes Lernen Künstliche Intelligenz (DE-588)4825546-4 gnd 7\p Lernendes System (DE-588)4120666-6 gnd 8\p Deep learning (DE-588)1135597375 gnd 9\p Soft Computing (DE-588)4455833-8 gnd |
topic_facet | Maschinelles Lernen Neuronales Netz Bestärkendes Lernen Künstliche Intelligenz Lernendes System Deep learning Soft Computing Hochschulschrift |
url | https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-238948 https://d-nb.info/130469884X/34 https://open.fau.de/handle/openfau/23894 |
work_keys_str_mv | AT porottiriccardo reinforcementlearningforquantumcontrolwithfeedback AT porottiriccardo bestarkendeslernenfurquantenkontrollemitruckkopplung |