Explainable representation learning of small quantum states

Unsupervised machine learning models build an internal representation of their training data without the need for explicit human guidance or feature engineering. This learned representation provides insights into which features of the data are relevant for the task at hand. In the context of quantum...

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Podrobná bibliografie

Hlavní autoři:	Felix Frohnert, Evert van Nieuwenburg
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IOP Publishing 2024-01-01
Edice:	Machine Learning: Science and Technology
Témata:	interpretable machine learning quantum physics representation learning of quantum systems
On-line přístup:	https://doi.org/10.1088/2632-2153/ad16a0
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