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Paper Citation Record · LEDGER

Learnable quantum spectral filters for hybrid graph neural networks

As of 7 August 2026, this Paper Citation Record lists 100 of 114 outbound references and 0 inbound Pith citation observations for arXiv:2507.05640.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.05640 v2

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measured 100 of 114 reference resolution

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100 of 114 outbound references displayed

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Outbound references

Observation 47874d6e-1b0d-441b-80d7-468959282daf · outbound

This paper cites Submission category by year, 2025.

Learnable quantum spectral filters for hybrid graph neural networks Submission category by year, 2025

Reference 1

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This paper cites GPT-4 Technical Report.

Learnable quantum spectral filters for hybrid graph neural networks GPT-4 Technical Report

Reference 2

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This paper cites DeepSeek-V3 Technical Report.

Learnable quantum spectral filters for hybrid graph neural networks DeepSeek-V3 Technical Report

Reference 3

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This paper cites A Comprehensive Overview of Large Language Models.

Learnable quantum spectral filters for hybrid graph neural networks A Comprehensive Overview of Large Language Models

Reference 4

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This paper cites Welcome to the era of chatgpt et al.

Learnable quantum spectral filters for hybrid graph neural networks Welcome to the era of chatgpt et al

Reference 5

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This paper cites A survey of sustainability in large language models: Applications, economics, and challenges.

Learnable quantum spectral filters for hybrid graph neural networks A survey of sustainability in large language models: Applications, economics, and challenges

Reference 6

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This paper cites Randomized algorithms.ACM Computing Surveys (CSUR), 28(1):33–37, 1996.

Learnable quantum spectral filters for hybrid graph neural networks Randomized algorithms.ACM Computing Surveys (CSUR), 28(1):33–37, 1996

Reference 7

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Observation 9bfc7952-ff1f-4894-abdc-3dbf2c9d2e92 · outbound

This paper cites Randomized algorithms for matrices and data.Foundations and Trends® in Machine Learning, 3(2):123–224, 2011.

Learnable quantum spectral filters for hybrid graph neural networks Randomized algorithms for matrices and data.Foundations and Trends® in Machine Learning, 3(2):123–224, 2011

Reference 8

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Observation 2bb2de9a-70f6-4d78-933e-0fa69fe16b5b · outbound

This paper cites A survey of randomized algorithms for training neural networks.Information Sciences, 364:146–155, 2016.

Learnable quantum spectral filters for hybrid graph neural networks A survey of randomized algorithms for training neural networks.Information Sciences, 364:146–155, 2016

Reference 9

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Observation fd565960-88a7-47f2-91d2-dc6fba4775ea · outbound

This paper cites Springer, 2001.

Learnable quantum spectral filters for hybrid graph neural networks Springer, 2001

Reference 10

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This paper cites Cambridge university press, 2011.

Learnable quantum spectral filters for hybrid graph neural networks Cambridge university press, 2011

Reference 11

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Observation fb2a3af8-6698-4be3-b370-293493a7ba63 · outbound

This paper cites Which problems have strongly exponential complexity?Journal of Computer and System Sciences, 63(4):512–530, 2001.

Learnable quantum spectral filters for hybrid graph neural networks Which problems have strongly exponential complexity?Journal of Computer and System Sciences, 63(4):512–530, 2001

Reference 12

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Observation e6d2fad3-2f29-4433-bf92-6cc7a90b5fa0 · outbound

This paper cites Computer architecture and amdahl’s law.Computer, 46(12):38–46, 2013.

Learnable quantum spectral filters for hybrid graph neural networks Computer architecture and amdahl’s law.Computer, 46(12):38–46, 2013

Reference 13

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Observation f981da73-4c8c-48df-b25b-d724fb97aea6 · outbound

This paper cites Amdahl’s law in the multicore era.Computer, 41(7):33–38, 2008.

Learnable quantum spectral filters for hybrid graph neural networks Amdahl’s law in the multicore era.Computer, 41(7):33–38, 2008

Reference 14

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This paper cites Qwen3 Technical Report.

Learnable quantum spectral filters for hybrid graph neural networks Qwen3 Technical Report

Reference 15

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This paper cites Num- ber 47.

Learnable quantum spectral filters for hybrid graph neural networks Num- ber 47

Reference 16

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Observation b1f41c29-cb30-463f-92f4-f9fab0de217d · outbound

This paper cites Expressive power of parametrized quantum circuits.Physical Review Research, 2(3):033125, 2020.

Learnable quantum spectral filters for hybrid graph neural networks Expressive power of parametrized quantum circuits.Physical Review Research, 2(3):033125, 2020

Reference 17

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Observation 8b982939-e200-4994-a14a-70096cb8e5f6 · outbound

This paper cites Expressivity of quantum neural networks.Physical Review Research, 3(3):L032049, 2021.

Learnable quantum spectral filters for hybrid graph neural networks Expressivity of quantum neural networks.Physical Review Research, 3(3):L032049, 2021

Reference 18

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Observation dbf84965-8eee-434b-9f59-c47bda8716d5 · outbound

This paper cites The power of quantum neural networks.Nature Computational Science, 1(6):403–409, 2021.

Learnable quantum spectral filters for hybrid graph neural networks The power of quantum neural networks.Nature Computational Science, 1(6):403–409, 2021

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This paper cites High-expressibility quantum neural networks using only classical resources.

Learnable quantum spectral filters for hybrid graph neural networks High-expressibility quantum neural networks using only classical resources

Reference 20

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This paper cites A new model for learning in graph domains.

Learnable quantum spectral filters for hybrid graph neural networks A new model for learning in graph domains

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This paper cites Graph neural networks for ranking web pages.

Learnable quantum spectral filters for hybrid graph neural networks Graph neural networks for ranking web pages

Reference 22

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Observation 91187175-abfe-4e55-acd2-f9a3b4cb5eb2 · outbound

This paper cites The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009.

Learnable quantum spectral filters for hybrid graph neural networks The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009

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This paper cites Learning skillful medium- range global weather forecasting.Science, 382(6677):1416–1421, 2023.

Learnable quantum spectral filters for hybrid graph neural networks Learning skillful medium- range global weather forecasting.Science, 382(6677):1416–1421, 2023

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Observation 490182fe-8fac-479c-9475-d60c44c6d68f · outbound

This paper cites A gentle intro- duction to graph neural networks.Distill, 6(9):e33, 2021.

Learnable quantum spectral filters for hybrid graph neural networks A gentle intro- duction to graph neural networks.Distill, 6(9):e33, 2021

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This paper cites Graph neural networks: A review of methods and applications.AI open, 1:57–81, 2020.

Learnable quantum spectral filters for hybrid graph neural networks Graph neural networks: A review of methods and applications.AI open, 1:57–81, 2020

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This paper cites Graph neural networks: Taxonomy, advances, and trends.ACM Transactions on Intelligent Systems and Technology (TIST), 13(1):1–54, 2022.

Learnable quantum spectral filters for hybrid graph neural networks Graph neural networks: Taxonomy, advances, and trends.ACM Transactions on Intelligent Systems and Technology (TIST), 13(1):1–54, 2022

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This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Learnable quantum spectral filters for hybrid graph neural networks Semi-Supervised Classification with Graph Convolutional Networks

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This paper cites Inductive representation learning on large graphs.

Learnable quantum spectral filters for hybrid graph neural networks Inductive representation learning on large graphs

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Observation 29938043-4965-47bd-be64-70191b2d0034 · outbound

This paper cites Graph attention networks.stat, 1050(20):10–48550, 2017.

Learnable quantum spectral filters for hybrid graph neural networks Graph attention networks.stat, 1050(20):10–48550, 2017

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This paper cites Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 2002.

Learnable quantum spectral filters for hybrid graph neural networks Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 2002

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Observation 40b731f8-704c-4346-89d8-a696375210ae · outbound

This paper cites Deep learning.nature, 521(7553):436–444, 2015.

Learnable quantum spectral filters for hybrid graph neural networks Deep learning.nature, 521(7553):436–444, 2015

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This paper cites Convolutional neural networks on graphs with fast localized spectral filtering.Advances in neural information processing systems, 29, 2016.

Learnable quantum spectral filters for hybrid graph neural networks Convolutional neural networks on graphs with fast localized spectral filtering.Advances in neural information processing systems, 29, 2016

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This paper cites Spectral Networks and Locally Connected Networks on Graphs.

Learnable quantum spectral filters for hybrid graph neural networks Spectral Networks and Locally Connected Networks on Graphs

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This paper cites Understanding convolutions on graphs.Distill, 6(9):e32, 2021.

Learnable quantum spectral filters for hybrid graph neural networks Understanding convolutions on graphs.Distill, 6(9):e32, 2021

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This paper cites Simplifying graph convolutional networks.

Learnable quantum spectral filters for hybrid graph neural networks Simplifying graph convolutional networks

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This paper cites Graph signal processing for machine learning: A review and new perspectives.IEEE Signal processing magazine, 37(6):117–127, 2020.

Learnable quantum spectral filters for hybrid graph neural networks Graph signal processing for machine learning: A review and new perspectives.IEEE Signal processing magazine, 37(6):117–127, 2020

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Observation 11477a8f-ce17-4ea8-8abb-5a851cb85901 · outbound

This paper cites Understanding Spectral Graph Neural Network.

Learnable quantum spectral filters for hybrid graph neural networks Understanding Spectral Graph Neural Network

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:28:58.851981Z digest=sha256:1269648639367c07b665df9af136fe303620dd4e4e8036b549183bf4a2a2df2e

Observation 0d36ee5f-02d2-4ace-8847-bd97ba1f0f3e · outbound

This paper cites Graphs, convolutions, and neural networks: From graph filters to graph neural networks.IEEE Signal Processing Magazine, 37(6):128– 138, 2020.

Learnable quantum spectral filters for hybrid graph neural networks Graphs, convolutions, and neural networks: From graph filters to graph neural networks.IEEE Signal Processing Magazine, 37(6):128– 138, 2020

Reference 39

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source=pdf_text observed=2026-08-06T19:28:58.938408Z digest=sha256:8bc64871316a2e254fdca0fdeb94d9fccc488e76d87ae57a164dc8bf810117e6

Observation 9b1e8ef1-128a-472e-b498-1ed4edadeffa · outbound

This paper cites A Survey on Spectral Graph Neural Networks.

Learnable quantum spectral filters for hybrid graph neural networks A Survey on Spectral Graph Neural Networks

Reference 40

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source=pdf_text observed=2026-08-06T19:28:59.076692Z digest=sha256:a42700e1a28862ffa48c13f4ec341ce41e98ad234c9cafb9db8f343fa3d1a34c

Observation 064bfd65-0430-43fa-b8f4-008ec517d1dd · outbound

This paper cites Taylornet: A novel approach for spectral filter learning on graph data.Neurocomputing, 605:128358, 2024.

Learnable quantum spectral filters for hybrid graph neural networks Taylornet: A novel approach for spectral filter learning on graph data.Neurocomputing, 605:128358, 2024

Reference 41

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source=pdf_text observed=2026-08-06T19:28:59.201005Z digest=sha256:21b2bbb5f12448d11caaff685b37a3a631a2f6b17d0558860937835027c77f3b

Observation 12f3e16f-4834-4598-9f63-f1921dafc9a8 · outbound

This paper cites Universal quantum circuit for n-qubit quantum gate: A programmable quantum gate.

Learnable quantum spectral filters for hybrid graph neural networks Universal quantum circuit for n-qubit quantum gate: A programmable quantum gate

Reference 42

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no resolver link, observed 2026-08-06T19:28:59.338810Z

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source=pdf_text observed=2026-08-06T19:28:59.338810Z digest=sha256:dd62744f37dd140bdd958c5f49a81ef5c20921b9d7391d4570ad2c73795a5f5d

Observation f2382976-6cae-4d5d-bab1-97dc80af3d5e · outbound

This paper cites Universal programmable quantum circuit schemes to emulate an operator.The Journal of chemical physics, 137(23), 2012.

Learnable quantum spectral filters for hybrid graph neural networks Universal programmable quantum circuit schemes to emulate an operator.The Journal of chemical physics, 137(23), 2012

Reference 43

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source=pdf_text observed=2026-08-06T19:28:59.419606Z digest=sha256:1298fb0ba4368bb6627391f8e0008ccfaca215dc726ac1a991f3445843f2062b

Observation 583fad1d-ea9e-4b3e-bc52-9ee9abacda5a · outbound

This paper cites A universal quantum circuit scheme for finding complex eigenvalues.Quantum information processing, 13:333–353, 2014.

Learnable quantum spectral filters for hybrid graph neural networks A universal quantum circuit scheme for finding complex eigenvalues.Quantum information processing, 13:333–353, 2014

Reference 44

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raw_fallback, observed 2026-08-06T19:29:21.255003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:28:59.510627Z digest=sha256:880e18a096b98b9b9899693521f60e703acda32d69611972d6e0807666a28324

Observation 1ca8fbee-650d-4c0f-9b14-ef552e1c5ef8 · outbound

This paper cites Parameterized quantum circuits as machine learning models.Quantum science and technology, 4(4):043001, 2019.

Learnable quantum spectral filters for hybrid graph neural networks Parameterized quantum circuits as machine learning models.Quantum science and technology, 4(4):043001, 2019

Reference 45

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raw_fallback, observed 2026-08-06T19:29:20.905220Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:28:59.654234Z digest=sha256:5bdb4680c17a88fb4e871c17d3a62d86eebd9c094674b03ab9ff438113c5081c

Observation e0126aa0-50a3-496c-9407-0a6d7fa6910e · outbound

This paper cites A variational eigenvalue solver on a photonic quantum processor.

Learnable quantum spectral filters for hybrid graph neural networks A variational eigenvalue solver on a photonic quantum processor

Reference 46

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no resolver link, observed 2026-08-06T19:28:59.745071Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:28:59.745071Z digest=sha256:5039b4bde4ccf650a2ca3da9f19f4cd96ce2623d6a6ecd15fa88019bc725e48d

Observation 52eca766-2619-464d-b7b2-b1ac04be178c · outbound

This paper cites The theory of varia- tional hybrid quantum-classical algorithms.New Journal of Physics, 18(2):023023, 2016.

Learnable quantum spectral filters for hybrid graph neural networks The theory of varia- tional hybrid quantum-classical algorithms.New Journal of Physics, 18(2):023023, 2016

Reference 47

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raw_fallback, observed 2026-08-06T19:29:20.606683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:28:59.848712Z digest=sha256:2b55a6e68ae16cd79fd3779431524ae34b57b16cbc8b0f9f508b81f7d59e6ee9

Observation 98b00c53-162e-4962-9169-eddf5381e36c · outbound

This paper cites Quantum Algorithms for Fixed Qubit Architectures.

Learnable quantum spectral filters for hybrid graph neural networks Quantum Algorithms for Fixed Qubit Architectures

Reference 48

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no resolver link, observed 2026-08-06T19:28:59.966783Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:28:59.966783Z digest=sha256:5b7114c54cb774e646fb06ab108fd2063242cab0df58900fd0969506591cfc9f

Observation 0a5485f3-ba38-4771-9c5d-372474057ed1 · outbound

This paper cites Natural parametrized quantum circuit.Physical Review A, 106(5):052611, 2022.

Learnable quantum spectral filters for hybrid graph neural networks Natural parametrized quantum circuit.Physical Review A, 106(5):052611, 2022

Reference 49

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raw_fallback, observed 2026-08-06T19:29:20.294714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:00.084104Z digest=sha256:f73e65a19aa1db270a5d7d667053c51576641f160633d81cbb725b6f927ae963

Observation 173fb40e-fafe-4440-a84f-d55ae5af3321 · outbound

This paper cites From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks.

Learnable quantum spectral filters for hybrid graph neural networks From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks

Reference 50

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no resolver link, observed 2026-08-06T19:29:00.250939Z

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source=pdf_text observed=2026-08-06T19:29:00.250939Z digest=sha256:c04afad7ba81e410333b0db18a216a76b8bbb7cb3f0630377a3cec0555fce7d6

Observation 7868bbe0-aa23-4baf-aa34-fd88849d74dc · outbound

This paper cites Quantum Graph Learning: Frontiers and Outlook.

Learnable quantum spectral filters for hybrid graph neural networks Quantum Graph Learning: Frontiers and Outlook

Reference 51

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verified exact
local_arxiv, observed 2026-08-06T19:29:09.874821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:00.354537Z digest=sha256:ad630cfd3c68181ae6fe89eeb7bed53c685a74123617e6d0ce16b0d1192cad41

Observation 9c076224-1ff5-4b78-8e9c-8747455da550 · outbound

This paper cites How can we naturally order and organize graph laplacian eigenvectors? In2018 IEEE Statistical Signal Processing Workshop (SSP), pages 483–487.

Learnable quantum spectral filters for hybrid graph neural networks How can we naturally order and organize graph laplacian eigenvectors? In2018 IEEE Statistical Signal Processing Workshop (SSP), pages 483–487

Reference 52

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raw_fallback, observed 2026-08-06T19:29:19.999670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:00.464136Z digest=sha256:27c0e8a198a5bd8f7fb09b9ac8e3f60272d02dfdd8d880b2be6069b27c9fdd9c

Observation 17263624-a07d-4bf2-b4cb-87f34eb72a3f · outbound

This paper cites The discrete cosine transform.SIAM review, 41(1):135–147, 1999.

Learnable quantum spectral filters for hybrid graph neural networks The discrete cosine transform.SIAM review, 41(1):135–147, 1999

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raw_fallback, observed 2026-08-06T19:29:19.792274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:00.605369Z digest=sha256:e84b740cffe01ab5db94415160c8e0436766060288021450f59d3e5f0b9c0e4c

Observation c1622c89-e8d2-4a80-9343-e01fa17b9cc6 · outbound

This paper cites Quantum Simulations Based on Parameterized Circuit of an Antisymmetric Matrix.

Learnable quantum spectral filters for hybrid graph neural networks Quantum Simulations Based on Parameterized Circuit of an Antisymmetric Matrix

Reference 54

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verified exact
local_arxiv, observed 2026-08-06T19:29:09.632535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:00.753258Z digest=sha256:7eac87eefff63578981d8b76d0d8f21156ac7343c0129703017a2a3eb9db9928

Observation 155b6204-b756-4c7c-b43f-840e6e683fe3 · outbound

This paper cites American Mathematical Soc., 1997.

Learnable quantum spectral filters for hybrid graph neural networks American Mathematical Soc., 1997

Reference 55

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no resolver link, observed 2026-08-06T19:29:00.896965Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:29:00.896965Z digest=sha256:688a25418e923353093a58cbd92345c2633c55cfcc880efc50ec5ab13cc1b4c9

Observation 8055a775-e6b0-4fe8-85c5-f922a88d7993 · outbound

This paper cites Laplacian matrices of graphs: a survey.Linear algebra and its applications, 197:143–176, 1994.

Learnable quantum spectral filters for hybrid graph neural networks Laplacian matrices of graphs: a survey.Linear algebra and its applications, 197:143–176, 1994

Reference 56

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raw_fallback, observed 2026-08-06T19:29:19.545033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:01.026986Z digest=sha256:704c500ece703c900a486e1148191b12b400ab4b0e9a2fd174404509efd62378

Observation 4766bee0-5e97-43ea-b5fc-6bba43eabe21 · outbound

This paper cites Algorithms, graph theory, and linear equations in laplacian matrices.

Learnable quantum spectral filters for hybrid graph neural networks Algorithms, graph theory, and linear equations in laplacian matrices

Reference 57

Resolution
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raw_fallback, observed 2026-08-06T19:29:19.328185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:01.135353Z digest=sha256:3766f614314bd8c8d97cb87d9387c5def614442b62183d51655c1ed7186573de

Observation 383cdcc7-8a5d-4480-9cf6-2616870c623b · outbound

This paper cites A tutorial on spectral clustering.Statistics and computing, 17:395–416, 2007.

Learnable quantum spectral filters for hybrid graph neural networks A tutorial on spectral clustering.Statistics and computing, 17:395–416, 2007

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no resolver link, observed 2026-08-06T19:29:01.252217Z

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source=pdf_text observed=2026-08-06T19:29:01.252217Z digest=sha256:729a30adacc2bb8439be80228303c6df5655287528cb285a994ee4a412d4d6e3

Observation f23b0351-2079-4102-81cf-c4415d279f7e · outbound

This paper cites Quantum spectral clustering through a biased phase estimation algorithm.TWMS Journal of Applied and Engineering Mathematics, 10(1):24–33, 2017.

Learnable quantum spectral filters for hybrid graph neural networks Quantum spectral clustering through a biased phase estimation algorithm.TWMS Journal of Applied and Engineering Mathematics, 10(1):24–33, 2017

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raw_fallback, observed 2026-08-06T19:29:19.085085Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:01.365154Z digest=sha256:672fdbb6d8512c2d87c62a6a86e29c79ba5420f73c05cbe331cd14f73605314e

Observation 66d2905c-7d27-4c17-b05a-eafd9e1c21b7 · outbound

This paper cites Convergence of laplacian eigenmaps.Advances in neural information processing systems, 19, 2006.

Learnable quantum spectral filters for hybrid graph neural networks Convergence of laplacian eigenmaps.Advances in neural information processing systems, 19, 2006

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raw_fallback, observed 2026-08-06T19:29:18.819116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:01.511972Z digest=sha256:967cd091889ee6b77e15619e65ec6aeeddd0bb0fa1caeda78f357cc989da567c

Observation e3382ba6-d272-474b-acd8-9eb7d9d44281 · outbound

This paper cites Manifold learning: What, how, and why.Annual Review of Statistics and Its Application, 11(1):393–417, 2024.

Learnable quantum spectral filters for hybrid graph neural networks Manifold learning: What, how, and why.Annual Review of Statistics and Its Application, 11(1):393–417, 2024

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raw_fallback, observed 2026-08-06T19:29:18.608687Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:01.699949Z digest=sha256:0b5c830c5349046893c25df15931aa97e456b04f3bb19e101163ce8e27d5105f

Observation 946643ba-a64c-4cec-9a8c-a0d061dcdcc1 · outbound

This paper cites A user guide to low-pass graph signal pro- cessing and its applications: Tools and applications.IEEE Signal Processing Magazine, 37(6):74–85, 2020.

Learnable quantum spectral filters for hybrid graph neural networks A user guide to low-pass graph signal pro- cessing and its applications: Tools and applications.IEEE Signal Processing Magazine, 37(6):74–85, 2020

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raw_fallback, observed 2026-08-06T19:29:18.349622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:01.852704Z digest=sha256:e9f6d679667a6ad7b904c88f13ecdfd7a78bae1366a9572fed4af3b8b1d1f854

Observation 86b7c5bd-ded1-409c-a38f-c2ebf2a7840b · outbound

This paper cites An Introduction to Convolutional Neural Networks.

Learnable quantum spectral filters for hybrid graph neural networks An Introduction to Convolutional Neural Networks

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:02.000903Z digest=sha256:7f40811c072d098c325a681767dae6f8dd710b3b558943611893dd2df2d659da

Observation 717fae10-8ccd-41a2-a71d-51465dbfb7e7 · outbound

This paper cites Introduction to convolutional neural networks.National Key Lab for Novel Software Technology.

Learnable quantum spectral filters for hybrid graph neural networks Introduction to convolutional neural networks.National Key Lab for Novel Software Technology

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raw_fallback, observed 2026-08-06T19:29:18.117100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:02.129735Z digest=sha256:15231431106cefce8c2a2b18b3c4dc0d6d6863b990b3918a543790b82305caca

Observation c97d06e5-4483-485b-9bd7-92fad0f95d36 · outbound

This paper cites A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 33(12):6999–7019, 2021.

Learnable quantum spectral filters for hybrid graph neural networks A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 33(12):6999–7019, 2021

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:29:02.305240Z digest=sha256:04c13e12a7f70b1b8a90d18a639b3abc16396b8dbfd812b031c9bf8eb3826a59

Observation f2c5282a-1168-4702-b41b-216abbaca773 · outbound

This paper cites Review of lightweight deep convolutional neural networks.Archives of Computational Methods in Engineering, 31(4):1915–1937, 2024.

Learnable quantum spectral filters for hybrid graph neural networks Review of lightweight deep convolutional neural networks.Archives of Computational Methods in Engineering, 31(4):1915–1937, 2024

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raw_fallback, observed 2026-08-06T19:29:17.873827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:02.468321Z digest=sha256:0af288ea249315c94e4aa1cbaff96f313643322c4933b84a2f9441aeb5d6b309

Observation 94b2236d-1916-428a-a656-8dae472071a0 · outbound

This paper cites Convolutional neural networks on graphs with chebyshev approximation, revisited.Advances in neural information processing systems, 35:7264–7276, 2022.

Learnable quantum spectral filters for hybrid graph neural networks Convolutional neural networks on graphs with chebyshev approximation, revisited.Advances in neural information processing systems, 35:7264–7276, 2022

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raw_fallback, observed 2026-08-06T19:29:17.691458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:02.567934Z digest=sha256:7cedac54c578295aeabd8652debbf187b34994baf3e17fa1c7696da1d1226a31

Observation da38fcc2-d478-41e4-88b0-b0ff9da0f54c · outbound

This paper cites Graph neural network, chebnet, graph convolutional network, and graph autoencoder: Tutorial and survey.

Learnable quantum spectral filters for hybrid graph neural networks Graph neural network, chebnet, graph convolutional network, and graph autoencoder: Tutorial and survey

Reference 68

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raw_fallback, observed 2026-08-06T19:29:17.511773Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:02.687322Z digest=sha256:42401e93586470661924ed0653105e75265f0ff973b9c95b0b8945c2bb49185f

Observation c3232043-ae35-43d8-b877-7719532245e8 · outbound

This paper cites Spectral representations for convolutional neural networks.Advances in neural information processing systems, 28, 2015.

Learnable quantum spectral filters for hybrid graph neural networks Spectral representations for convolutional neural networks.Advances in neural information processing systems, 28, 2015

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raw_fallback, observed 2026-08-06T19:29:17.240188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:02.827661Z digest=sha256:95b63a1a1eb3ab786496a03bf91bde222c5e911cf5e2b98362b36c5217e43a02

Observation f62c29c3-7f25-492c-8b15-ef84397e97b6 · outbound

This paper cites On the stability of polynomial spectral graph fil- ters.

Learnable quantum spectral filters for hybrid graph neural networks On the stability of polynomial spectral graph fil- ters

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raw_fallback, observed 2026-08-06T19:29:17.028877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:02.931991Z digest=sha256:ad2eebcf4f9e0d3cf67503bc7ba34c14530a88aa2efb5cafaf92e24ea469d663

Observation 87ddc19c-8f98-48c3-a255-ba86b3d01631 · outbound

This paper cites JHU press, 2013.

Learnable quantum spectral filters for hybrid graph neural networks JHU press, 2013

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unresolved
no resolver link, observed 2026-08-06T19:29:03.055762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:03.055762Z digest=sha256:12bb9b5ad9c22e04710473188d75b0465fc3c34ff26dc3cab194c9f605048283

Observation b7a8c060-ad7f-402e-aff9-7f7fc5209db4 · outbound

This paper cites Wavelets on graphs via spectral graph theory.Applied and Computational Harmonic Analysis, 30(2):129–150, 2011.

Learnable quantum spectral filters for hybrid graph neural networks Wavelets on graphs via spectral graph theory.Applied and Computational Harmonic Analysis, 30(2):129–150, 2011

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raw_fallback, observed 2026-08-06T19:29:16.770470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.155698Z digest=sha256:c7de800e3a79343983f45bf10eb0917dc1ad83e96eedc02ba7e8554373dd0156

Observation b9dcf73d-43a6-41d8-a4df-2f36fde1c22a · outbound

This paper cites Revisiting convolutional neural network on graphs with polynomial approximations of laplace–beltrami spectral filtering.Neural Computing and Applications, 33:13693–13704, 2021.

Learnable quantum spectral filters for hybrid graph neural networks Revisiting convolutional neural network on graphs with polynomial approximations of laplace–beltrami spectral filtering.Neural Computing and Applications, 33:13693–13704, 2021

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verified fuzzy
raw_fallback, observed 2026-08-06T19:29:16.503564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.299582Z digest=sha256:0df98e9ab10fbc56bfaa483e5488851b72cfb48f38b6309cd5e2007786ac270f

Observation 5e5fb737-656e-45f2-9f11-8d6a23f67a75 · outbound

This paper cites Quantum convolutional neural networks.Nature Physics, 15(12):1273–1278, 2019.

Learnable quantum spectral filters for hybrid graph neural networks Quantum convolutional neural networks.Nature Physics, 15(12):1273–1278, 2019

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raw_fallback, observed 2026-08-06T19:29:16.192030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.459444Z digest=sha256:77f4a4f44163b2ce082f1889364150bfbd1fa4fbba2ce2b6d8cd23a46cc052f0

Observation bed9a070-e90d-477f-8d8a-bee8f95b41a4 · outbound

This paper cites A tutorial on quantum convolutional neural networks (qcnn).

Learnable quantum spectral filters for hybrid graph neural networks A tutorial on quantum convolutional neural networks (qcnn)

Reference 75

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raw_fallback, observed 2026-08-06T19:29:15.903228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.553633Z digest=sha256:e684ff166b63cdc4ecd8a8c6cdb2fb4dde9f560f1e2df54aaf4890ee6b939673

Observation c0b69124-175a-4e55-9c7e-6b6826a8f97a · outbound

This paper cites Quantum convo- lutional neural networks for high energy physics data analysis.Physical Review Research, 4(1):013231, 2022.

Learnable quantum spectral filters for hybrid graph neural networks Quantum convo- lutional neural networks for high energy physics data analysis.Physical Review Research, 4(1):013231, 2022

Reference 76

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raw_fallback, observed 2026-08-06T19:29:15.716653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.659537Z digest=sha256:6a826baa241891d875c151990db0471de8d1190fbc908eba8d4aafecd1858367

Observation 7d24ce8e-da40-4926-a70b-ff910026e28e · outbound

This paper cites Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases.Nature communications, 13(1):4144, 2022.

Learnable quantum spectral filters for hybrid graph neural networks Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases.Nature communications, 13(1):4144, 2022

Reference 77

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raw_fallback, observed 2026-08-06T19:29:15.497299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.776037Z digest=sha256:9a57ef491b953f844b47a787930f864e97c5175dfefb7584ce541e4b56818df3

Observation 1b0ec24c-1074-4d24-8591-8d728f439a1e · outbound

This paper cites What can we learn from quantum convolutional neural networks?Advanced Quantum Technologies, page 2400325, 2023.

Learnable quantum spectral filters for hybrid graph neural networks What can we learn from quantum convolutional neural networks?Advanced Quantum Technologies, page 2400325, 2023

Reference 78

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raw_fallback, observed 2026-08-06T19:29:15.276885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.895661Z digest=sha256:468922c6a900e0f97ed482d5a99dd05fd4dff0fb2d18a3423697f8b0361eaa6c

Observation 990abaf9-69a2-431e-992d-324989ad212a · outbound

This paper cites Hybrid quantum-classical convolutional neural networks.Science China Physics, Mechanics & Astronomy, 64(9):290311, 2021.

Learnable quantum spectral filters for hybrid graph neural networks Hybrid quantum-classical convolutional neural networks.Science China Physics, Mechanics & Astronomy, 64(9):290311, 2021

Reference 79

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raw_fallback, observed 2026-08-06T19:29:15.013168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:03.984931Z digest=sha256:d3b8d8d2708bb46d35f373aa9908afca566b2eee88e41bfe44921a76f663d903

Observation 4647e3fa-d919-4a16-a7dd-6593510e3174 · outbound

This paper cites Quantum convolutional neural networks for multi-channel supervised learning.Quantum Machine Intelligence, 5(2):41, 2023.

Learnable quantum spectral filters for hybrid graph neural networks Quantum convolutional neural networks for multi-channel supervised learning.Quantum Machine Intelligence, 5(2):41, 2023

Reference 80

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raw_fallback, observed 2026-08-06T19:29:14.776065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:04.099449Z digest=sha256:f76bb54798c430385857c566bd73b6def52a9075b67015ab6f3b591f912ea67e

Observation d8ead58d-b166-4d1a-8e37-b0b529777048 · outbound

This paper cites Classical-to-quantum convolutional neural network transfer learning.Neurocomputing, 555:126643, 2023.

Learnable quantum spectral filters for hybrid graph neural networks Classical-to-quantum convolutional neural network transfer learning.Neurocomputing, 555:126643, 2023

Reference 81

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raw_fallback, observed 2026-08-06T19:29:14.547372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:04.254437Z digest=sha256:7704c61232697cbebfa73a3508be32ad392f80084a2c0578a69df8e30b743a54

Observation 3d9cc071-16a8-4942-bb09-917c0a25be47 · outbound

This paper cites Quantum convolutional neural network based on variational quantum circuits.Optics Communications, 550:129993, 2024.

Learnable quantum spectral filters for hybrid graph neural networks Quantum convolutional neural network based on variational quantum circuits.Optics Communications, 550:129993, 2024

Reference 82

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raw_fallback, observed 2026-08-06T19:29:14.303342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:04.348500Z digest=sha256:05bbe581498d1b8428186e9d4fca6d43fede24fbda4a58542f0a2e5173ca4e39

Observation 5ed28cec-c950-47e3-9fb9-78d38c3aee32 · outbound

This paper cites Quantum Algorithms for Deep Convolutional Neural Networks.

Learnable quantum spectral filters for hybrid graph neural networks Quantum Algorithms for Deep Convolutional Neural Networks

Reference 83

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no resolver link, observed 2026-08-06T19:29:04.480697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:04.480697Z digest=sha256:e9f9496a3bad8a9555daf0435fae7090b28e17e2537d8ad3404ce09eedc9708b

Observation 256b39bc-bc06-4eec-b633-b834d51142b1 · outbound

This paper cites Quantum optical convolutional neural network: a novel image recognition framework for quantum computing.IEEE access, 9:103337–103346, 2021.

Learnable quantum spectral filters for hybrid graph neural networks Quantum optical convolutional neural network: a novel image recognition framework for quantum computing.IEEE access, 9:103337–103346, 2021

Reference 84

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raw_fallback, observed 2026-08-06T19:29:14.089003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:04.600792Z digest=sha256:5371e60a50a38635ed5c5495df9322cf5a45cf531caeeb9385c7a242dfaea55c

Observation 715f99e6-e8ff-41b4-83d8-12ca2dfa06ee · outbound

This paper cites Quantum Convolutional Neural Networks are Effectively Classically Simulable.

Learnable quantum spectral filters for hybrid graph neural networks Quantum Convolutional Neural Networks are Effectively Classically Simulable

Reference 85

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no resolver link, observed 2026-08-06T19:29:04.694639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:04.694639Z digest=sha256:1dc16de472d8461a26c07b9195eea51891de8c8926b624fbdb853dfb05dc15a7

Observation bcba1630-4212-4f33-8ed2-8eec593a773c · outbound

This paper cites Efficient classical simulation of random shallow 2d quantum circuits.Physical Review X, 12(2):021021, 2022.

Learnable quantum spectral filters for hybrid graph neural networks Efficient classical simulation of random shallow 2d quantum circuits.Physical Review X, 12(2):021021, 2022

Reference 86

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verified fuzzy
raw_fallback, observed 2026-08-06T19:29:13.861294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:04.795645Z digest=sha256:23d4cf57d44e972c4a9c87aa3056d130315219498e1bcbf8f51574118ce9e64f

Observation 9670067a-a888-4d8b-ba1e-dd0cf22c06ee · outbound

This paper cites Quantum Graph Neural Networks.

Learnable quantum spectral filters for hybrid graph neural networks Quantum Graph Neural Networks

Reference 87

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no resolver link, observed 2026-08-06T19:29:04.948196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:04.948196Z digest=sha256:db90701f7900f8d838f40ead9a22ac3f5c4ec401fed7ef65322fa074e9062739

Observation 7ee1cf21-d779-44dd-aac4-5d152d9c1f0a · outbound

This paper cites A Quantum Approximate Optimization Algorithm.

Learnable quantum spectral filters for hybrid graph neural networks A Quantum Approximate Optimization Algorithm

Reference 88

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no resolver link, observed 2026-08-06T19:29:05.082070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:05.082070Z digest=sha256:9a647a15109ea2a53e2ceb28132d68d9bc70499b00fdd4e3b649475ad79e05b8

Observation ca86fc88-c336-4662-ba84-56c4249043da · outbound

This paper cites From the quantum approximate optimization algorithm to a quantum alternating operator ansatz.Algorithms, 12(2):34, 2019.

Learnable quantum spectral filters for hybrid graph neural networks From the quantum approximate optimization algorithm to a quantum alternating operator ansatz.Algorithms, 12(2):34, 2019

Reference 89

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no resolver link, observed 2026-08-06T19:29:05.217938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:05.217938Z digest=sha256:e95e70b6c9bec9ab90b6544f570ac61cfffa5840c63280d638cd966531b12624

Observation 75666890-3800-4b67-914b-a4136129360e · outbound

This paper cites Quantum-based subgraph convolutional neural networks.Pattern Recognition, 88:38–49, 2019.

Learnable quantum spectral filters for hybrid graph neural networks Quantum-based subgraph convolutional neural networks.Pattern Recognition, 88:38–49, 2019

Reference 90

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raw_fallback, observed 2026-08-06T19:29:13.598980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:05.370011Z digest=sha256:cad067d4ceb51979638af0414b6b89300499e80c9662dc6930c47f6c33dcbd1b

Observation cda199e5-13a1-41dd-b779-770af9e1b41e · outbound

This paper cites On the design of quantum graph convolutional neural network in the nisq-era and beyond.

Learnable quantum spectral filters for hybrid graph neural networks On the design of quantum graph convolutional neural network in the nisq-era and beyond

Reference 91

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raw_fallback, observed 2026-08-06T19:29:13.366382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:05.544920Z digest=sha256:20b207bea3d774de5e4ab4900ffa3e165085e0b16ddb2c389e659c167d2fb098

Observation 44b9d395-a971-4d8f-819a-01dba320920a · outbound

This paper cites A quantum spatial graph convolu- tional neural network model on quantum circuits.IEEE Transactions on Neural Networks and Learning Systems, 2024.

Learnable quantum spectral filters for hybrid graph neural networks A quantum spatial graph convolu- tional neural network model on quantum circuits.IEEE Transactions on Neural Networks and Learning Systems, 2024

Reference 92

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raw_fallback, observed 2026-08-06T19:29:13.168907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:05.640206Z digest=sha256:34632a8ad7690adaab566f36a1cddd96585a59d9e4953ea1bdef8f1a99f75f7f

Observation f49304a0-ee64-4bc4-a23e-3f797fdc33b5 · outbound

This paper cites Financial fraud detection using quantum graph neural networks.Quantum Machine Intelligence, 6(1):7, 2024.

Learnable quantum spectral filters for hybrid graph neural networks Financial fraud detection using quantum graph neural networks.Quantum Machine Intelligence, 6(1):7, 2024

Reference 93

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raw_fallback, observed 2026-08-06T19:29:12.961278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:05.753424Z digest=sha256:950b896fa67f87bde92001dc30122a236d3b25134eebad74e5c96b6a4f03b16b

Observation 2eb94d19-5fd7-4f93-942a-4de1e129d921 · outbound

This paper cites Quantum graph neural network models for materials search.Materials, 16(12):4300, 2023.

Learnable quantum spectral filters for hybrid graph neural networks Quantum graph neural network models for materials search.Materials, 16(12):4300, 2023

Reference 94

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raw_fallback, observed 2026-08-06T19:29:12.725927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:05.881296Z digest=sha256:77c7e2b87ed27e6af0318a7dca27fb441b1151310f7ed18ad1c9f160c3fe1e8e

Observation 4609e3b4-87f7-48dc-9c76-dd875cc3ecf9 · outbound

This paper cites A unifying primary framework for qgnns from quantum graph states.The European Physical Journal Special Topics, pages 1–10, 2024.

Learnable quantum spectral filters for hybrid graph neural networks A unifying primary framework for qgnns from quantum graph states.The European Physical Journal Special Topics, pages 1–10, 2024

Reference 95

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raw_fallback, observed 2026-08-06T19:29:12.506759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:06.004160Z digest=sha256:96716023c418c205cbe680c9e10a313cef44b43e7f2f71f06c7a41a41cfeb17b

Observation 23982e64-c6e3-4408-acee-97f439cc03a0 · outbound

This paper cites Ground state-based quantum feature maps.

Learnable quantum spectral filters for hybrid graph neural networks Ground state-based quantum feature maps

Reference 96

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no resolver link, observed 2026-08-06T19:29:06.124469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:06.124469Z digest=sha256:8e5c15f0fd97ddf8193330f20e081cf0e3311014b5b20c6b30c07fbfed1c44ae

Observation 3c00298b-130b-49c0-a2bd-667b58f87444 · outbound

This paper cites Iterative Quantum Feature Maps.

Learnable quantum spectral filters for hybrid graph neural networks Iterative Quantum Feature Maps

Reference 97

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no resolver link, observed 2026-08-06T19:29:06.250765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:06.250765Z digest=sha256:b5b0d29528667111ba738c2700dfa1ed71e93a1ba7e4418ae46e86ce192f58f1

Observation 101a23f9-2327-43a4-af85-5a6555a62d6e · outbound

This paper cites Efficient quantum feature extraction for cnn-based learning.

Learnable quantum spectral filters for hybrid graph neural networks Efficient quantum feature extraction for cnn-based learning

Reference 98

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raw_fallback, observed 2026-08-06T19:29:12.301867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:06.353931Z digest=sha256:525bb72c1562839f91ac3aa9ef2b2a50417cf1901827aba65740bffc84b6ad48

Observation b1cce699-5483-4e57-b8a3-eeba682d2686 · outbound

This paper cites Hybrid Quantum-Classical Graph Convolutional Network.

Learnable quantum spectral filters for hybrid graph neural networks Hybrid Quantum-Classical Graph Convolutional Network

Reference 99

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no resolver link, observed 2026-08-06T19:29:06.474673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:29:06.474673Z digest=sha256:8a8f2b5bdf618d660ce6a480826fe221b1ea12cde9c49834a7bd3b53bc33899b

Observation e45ab4df-8f9c-49a2-a82d-0e7d27db4219 · outbound

This paper cites Quantum graph as a quantum spectral filter.Journal of Mathematical Physics, 54(3), 2013.

Learnable quantum spectral filters for hybrid graph neural networks Quantum graph as a quantum spectral filter.Journal of Mathematical Physics, 54(3), 2013

Reference 100

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raw_fallback, observed 2026-08-06T19:29:12.048377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:29:06.583136Z digest=sha256:d98297f7933560f2656d8aba4da756d7916c71152e548c587e5427f62d225e2d

Pith citing papers

No inbound Pith citation observations are available.