Cited by 26Quantum Computing Algorithms and ArchitectureNeural Networks and ApplicationsQuantum many-body systems

Quantum deep learning neural networks

Kamruzzaman, Abu, Alhwaiti, Yousef, Leider, Avery, Tappert, Charles C.·2020·Lecture notes in networks and systems

Integrity signals

Registry

Crossref · 10.1007/978-3-030-12385-7_24

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Kamruzzaman, A., Alhwaiti, Y., Leider, A., & Tappert, C. C.
Affiliations
Pace University (US)
Corresponding author
Kamruzzaman, Abu
Venue
Lecture notes in networks and systems
Published
2019-02-02
Pages
299-311
ISSN
  • 2367-3370 (ISSN-L)
  • 2367-3389
OpenAlex
W2916082654
Cited by
26
References
27
Citations by year
2026: 1 · 2025: 6 · 2024: 3 · 2023: 4 · 2022: 4 · 2021: 3 · 2020: 3 · 2019: 2
FWCI
1.12
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in networks and systems (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
  • Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
Keywords
quantum neural networks, quantum deep learning, quantum computing hardware, quantum perceptron, nonlinear activation functions

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review