Benchmarking Neural Networks For Quantum Computations

The power of quantum computers is still somewhat speculative. Although they are certainly faster than classical ones at some tasks, the class of problems they can efficiently solve has not been mapped definitively onto known classical complexity theory. This means that we do not know for which calcu...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 31; H. 7; S. 2522 - 2531
Hauptverfasser:	Nguyen, Nam H., Behrman, E. C., Moustafa, Mohamed A., Steck, J. E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Benchmark testing Benchmarking Biological neural networks complex neural network complexity Complexity theory Computer simulation Computers entanglement Learning algorithms Machine learning Neural networks quantum computation Quantum computers Quantum computing Quantum entanglement quantum machine learning quantum neural network
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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