Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection | Paper Citation Record

Observation 8a5c8d0b-68be-469e-9752-10c7e7bf5223 · outbound

This paper cites The future of machine learning in astronomy: A perspective,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The future of machine learning in astronomy: A perspective,

Reference 1

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This paper cites Machine learning in astronomy: A practical overview,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Machine learning in astronomy: A practical overview,

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Observation cacaed7e-9010-4ebe-8f0d-0ee52b64e436 · outbound

This paper cites A quantum-enhanced support vector machine for galaxy classification,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection A quantum-enhanced support vector machine for galaxy classification,

Reference 3

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This paper cites Data analysis for gravitational waves using neural networks on quan- tum computers,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Data analysis for gravitational waves using neural networks on quan- tum computers,

Reference 4

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This paper cites Machine learning of high dimensional data on a noisy quantum processor,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Machine learning of high dimensional data on a noisy quantum processor,

Reference 5

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This paper cites Machine learning and the physical sciences,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Machine learning and the physical sciences,

Reference 6

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Observation cfff5634-474d-4bea-8c96-ff7cfb1d02eb · outbound

This paper cites Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection

Reference 7

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Observation ab6823d9-7131-4ced-b4ae-e0c7095ca8b4 · outbound

This paper cites Short versus long gamma-ray bursts: spectra, energetics, and luminosities,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Short versus long gamma-ray bursts: spectra, energetics, and luminosities,

Reference 8

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Observation 2bfc102b-c868-4783-80f4-e811fa3e821c · outbound

This paper cites Probing cosmic chemical evo- lution with gamma-ray bursts: grb060206 at z=4.048,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Probing cosmic chemical evo- lution with gamma-ray bursts: grb060206 at z=4.048,

Reference 9

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Observation 21bd9ddc-2cb2-4874-9fdb-853842a458a8 · outbound

This paper cites Multi-Messenger Astronomy with GRBs: A White Paper for the Astro2010 Decadal Survey,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Multi-Messenger Astronomy with GRBs: A White Paper for the Astro2010 Decadal Survey,

Reference 10

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Observation e06c388f-daa1-40b9-a5d1-b745d122e775 · outbound

This paper cites Fermi Gamma-ray Space Telescope.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Fermi Gamma-ray Space Telescope

Reference 11

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Observation aecc8dc8-5dca-4c20-96a6-871338200408 · outbound

This paper cites The Fourth Fermi-GBM Gamma-Ray Burst Catalog: A Decade of Data.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The Fourth Fermi-GBM Gamma-Ray Burst Catalog: A Decade of Data

Reference 12

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Observation 807dd3b1-4d15-479f-abb3-a5f736234bce · outbound

This paper cites The Fermi GBM Gamma-Ray Burst Spectral Catalog: 10 Years of Data.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The Fermi GBM Gamma-Ray Burst Spectral Catalog: 10 Years of Data

Reference 13

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Observation c35e0995-1ec1-450c-9df1-f51ccd92a247 · outbound

This paper cites The Swift Gamma-Ray Burst Mission.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The Swift Gamma-Ray Burst Mission

Reference 14

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This paper cites The AGILE Mission,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The AGILE Mission,

Reference 15

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This paper cites The Second AGILE MCAL Gamma-Ray Burst Catalog: 13 yr of Observations,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The Second AGILE MCAL Gamma-Ray Burst Catalog: 13 yr of Observations,

Reference 16

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Observation 1bff7bac-0444-4739-a435-c8fae9b1cbbf · outbound

This paper cites an unresolved cited work.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Unresolved cited work

Reference 17

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Observation e026de3b-2166-457f-abd6-d8db681b4bb8 · outbound

This paper cites Survey of encoding techniques for quantum machine learning,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Survey of encoding techniques for quantum machine learning,

Reference 18

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Observation 9de69c91-9958-49f1-b14b-cdfd45632414 · outbound

This paper cites Quantum machine learning: Ex- ploring the role of data encoding techniques, challenges, and future directions,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum machine learning: Ex- ploring the role of data encoding techniques, challenges, and future directions,

Reference 19

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Observation abc4b56e-2e8f-4dc4-bb0f-83d95e367237 · outbound

This paper cites Quantum data encoding as a distinct abstraction layer in the design of quantum circuits,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum data encoding as a distinct abstraction layer in the design of quantum circuits,

Reference 20

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This paper cites Data rotation and its influence on quantum encoding,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Data rotation and its influence on quantum encoding,

Reference 21

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Observation e79e5fa6-a286-4aaa-9492-edffe58ec48e · outbound

This paper cites Hybrid quantum encoding: Combining amplitude and basis encoding for enhanced data storage and processing in quantum com- puting,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Hybrid quantum encoding: Combining amplitude and basis encoding for enhanced data storage and processing in quantum com- puting,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:39:02.371944Z

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Observation a10098eb-25b0-4211-9f4b-8570e6f3cc86 · outbound

This paper cites Hybrid classical-quantum transfer learning for text classification,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Hybrid classical-quantum transfer learning for text classification,

Reference 23

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Observation 7624876f-e837-4c58-a308-d0c49d05f02d · outbound

This paper cites Towards autoqml: A cloud- based automated circuit architecture search framework,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Towards autoqml: A cloud- based automated circuit architecture search framework,

Reference 24

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Observation 28da9602-3022-44e1-a01c-c0a3c6ff08f7 · outbound

This paper cites Resource frugal optimizer for quantum machine learning,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Resource frugal optimizer for quantum machine learning,

Reference 25

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Observation 06c9a12a-53d6-45a6-8996-77b2df7ed888 · outbound

This paper cites Quantifying the performance of quantum machine learning algorithms for heart valve detection using h- bert classifier,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantifying the performance of quantum machine learning algorithms for heart valve detection using h- bert classifier,

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Observation 7469b43e-a32c-47cc-948b-0ac0d99103ed · outbound

This paper cites General- ization in quantum machine learning from few training data,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection General- ization in quantum machine learning from few training data,

Reference 27

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Observation 251d8ce6-0546-445f-9668-ee869fdeeca1 · outbound

This paper cites Surveying the reach and maturity of machine learning and artificial intelligence in astronomy,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Surveying the reach and maturity of machine learning and artificial intelligence in astronomy,

Reference 28

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Observation 15e0639d-c75e-4ee0-97b6-bfac8856048f · outbound

This paper cites Quantum-enhanced support vector machines for galaxy classification,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum-enhanced support vector machines for galaxy classification,

Reference 29

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Observation e7755ca8-66ec-4b06-bc21-5a1f1042ff04 · outbound

This paper cites Quantum neural networks in radio astronomy: Pulsar classification,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum neural networks in radio astronomy: Pulsar classification,

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Observation ded6b358-3e84-429f-91ad-7a2c55b88b10 · outbound

This paper cites Quantum machine learning: A re- view and current status,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum machine learning: A re- view and current status,

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This paper cites New trends in quan- tum machine learning,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection New trends in quan- tum machine learning,

Reference 32

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This paper cites Comparing quantum and clas- sical machine learning for vector boson scattering background reduction at the large hadron collider,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Comparing quantum and clas- sical machine learning for vector boson scattering background reduction at the large hadron collider,

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This paper cites Available: https://www.scopus.com/record/ display.uri?eid=2- s2.0- 85168313271%5C&origin= scopusAI.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Available: https://www.scopus.com/record/ display.uri?eid=2- s2.0- 85168313271%5C&origin= scopusAI

Reference 34

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Observation 384c8bfe-dd45-4c96-b4a5-f38e1717f44f · outbound

This paper cites The state of quantum learning: A comparative review towards classical machine learning,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection The state of quantum learning: A comparative review towards classical machine learning,

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Observation e6b0c90c-e8d5-4011-b91b-ce64f58d7b6c · outbound

This paper cites Image data augmentation for the taiga-iact experiment with conditional generative adversarial networks,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Image data augmentation for the taiga-iact experiment with conditional generative adversarial networks,

Reference 36

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This paper cites Parallel hybrid quantum-classical machine learning for kernelized time- series classification,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Parallel hybrid quantum-classical machine learning for kernelized time- series classification,

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Observation a1566241-a799-4ce8-9baf-0f0df2fdfd8a · outbound

This paper cites Data re-uploading for a universal quantum classifier,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Data re-uploading for a universal quantum classifier,

Reference 38

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Observation d1cfaecf-9d47-40c1-b353-fa1c760aae5a · outbound

This paper cites Effect of data encoding on the expressive power of variational quantum-machine-learning models,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Effect of data encoding on the expressive power of variational quantum-machine-learning models,

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This paper cites Schuld and F.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Schuld and F

Reference 40

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This paper cites Quantum Fingerprinting and Quantum Hashing. Computational and Cryptographical Aspects,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum Fingerprinting and Quantum Hashing. Computational and Cryptographical Aspects,

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Observation 441db88f-0c85-4d72-aef9-aa7a9dfa34e9 · outbound

This paper cites Hybrid classical–quantum text search based on hashing,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Hybrid classical–quantum text search based on hashing,

Reference 42

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Observation 70f90827-b902-4493-8801-a55dd9ac0985 · outbound

This paper cites Quantum fingerprinting,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Quantum fingerprinting,

Reference 43

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Observation 4962fc2d-bbfe-4af4-b05d-e2d8b536762e · outbound

This paper cites Khadiev, A.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Khadiev, A

Reference 44

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This paper cites GAPs for Shallow Implementation of Quantum Fi- nite Automata,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection GAPs for Shallow Implementation of Quantum Fi- nite Automata,

Reference 45

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Observation 47c07a5f-3a0f-4f23-bf90-12f1b4c9cad9 · outbound

This paper cites Efficient implementation of amplitude form of quantum hashing using state-of-the-art quantum processors,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Efficient implementation of amplitude form of quantum hashing using state-of-the-art quantum processors,

Reference 46

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Observation 32ac3b49-a1d7-4dc0-953d-6ec7832ba89e · outbound

This paper cites General parameter-shift rules for quantum gradients,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection General parameter-shift rules for quantum gradients,

Reference 47

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This paper cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,

Reference 48

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Observation 5e4e648f-a84c-4833-9685-4b7fb6af4dc4 · outbound

This paper cites Ex- pressibility and entangling capability of parameter- ized quantum circuits for hybrid quantum-classical al- gorithms,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Ex- pressibility and entangling capability of parameter- ized quantum circuits for hybrid quantum-classical al- gorithms,

Reference 49

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This paper cites An overview of the simultaneous perturba- tion method for efficient optimization,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection An overview of the simultaneous perturba- tion method for efficient optimization,

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:38:58.492710Z

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Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Unresolved cited work

Reference 51

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Observation 0fbc952b-c975-4092-b97b-b6a4d20c693d · outbound

This paper cites Pegasos: Primal estimated sub-gradient solver for svm,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Pegasos: Primal estimated sub-gradient solver for svm,

Reference 52

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This paper cites Evolution of data formats in very-high-energy gamma-ray astron- omy,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Evolution of data formats in very-high-energy gamma-ray astron- omy,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:38:57.743617Z

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This paper cites Acero, J.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Acero, J

Reference 54

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This paper cites Gammapy: A python package for gamma-ray astronomy,.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Gammapy: A python package for gamma-ray astronomy,

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Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Unresolved cited work

Reference 56

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Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Technology and Performance Benchmarks of IQM's 20-Qubit Quantum Computer

Reference 57

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Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Searching for very-high-energy electromagnetic counterparts to gravitational-wave events with the Cherenkov Telescope Array

Reference 58

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This paper cites 1109 / ICCIT58146.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection 1109 / ICCIT58146

Reference 127

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Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection 3103 / S002713462401004X

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