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Paper Citation Record · LEDGER

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation

As of 23 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.13897.

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

pith.paper-citation-record.v1
2607.13897 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:27:05.131993Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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  • unresolved36
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa8bb146-39c3-4213-bafd-8d2e938bc286 · outbound

This paper cites Intelligent Jamming Strategies for Secure Spectrum Sharing Systems,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Intelligent Jamming Strategies for Secure Spectrum Sharing Systems,

Reference 1

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source=pdf_text observed=2026-08-02T03:27:04.997541Z digest=sha256:447921b3b90d8dee77b3b68baa95db1bae8d3cd18bed8c4dcf604b55562a8b63

Observation 0a7b3950-08c2-4000-a176-c7c32a7bee92 · outbound

This paper cites A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends,

Reference 2

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source=pdf_text observed=2026-08-02T03:27:05.002429Z digest=sha256:e51c6764a911600465b0b41dbf77767bc6fa23f92f82f6bbc022150928d68167

Observation 9271270d-7f91-42b1-90e0-26265470b42f · outbound

This paper cites RF Jamming Dataset: A Wireless Spectral Scan Approach for Malicious Interference Detection,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation RF Jamming Dataset: A Wireless Spectral Scan Approach for Malicious Interference Detection,

Reference 3

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source=pdf_text observed=2026-08-02T03:27:05.006399Z digest=sha256:997a31dd0af229b3a5995d7c32bec2e7a65f2f746d4cfbee74779c39d301d7f5

Observation 75283e26-7612-4eeb-af70-51928b298faa · outbound

This paper cites LTE/LTE-A Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation LTE/LTE-A Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation,

Reference 4

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source=pdf_text observed=2026-08-02T03:27:05.010533Z digest=sha256:7b2aa781b5c352ee49dbebf11ee3df929b0b4ddc84281e8ab4ec3f1ba67da267

Observation 4687f9ae-c30b-4212-a461-995f60fc1840 · outbound

This paper cites A Communications Jamming Taxonomy,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation A Communications Jamming Taxonomy,

Reference 5

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source=pdf_text observed=2026-08-02T03:27:05.014703Z digest=sha256:a5b65c9d4c5a826fd62a264df75753a2ec8cd77e8a082c7f113082f89c2964de

Observation bf7e4773-4827-4a0e-bf47-beb7799bedaf · outbound

This paper cites Jamming Attacks and Anti-Jamming Strategies in Wireless Networks: A Comprehensive Survey,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Jamming Attacks and Anti-Jamming Strategies in Wireless Networks: A Comprehensive Survey,

Reference 6

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source=pdf_text observed=2026-08-02T03:27:05.018751Z digest=sha256:da351e9a7f8bc0b42353f2aa7317e375d9c85c93a011ce0bb95aaa8fc90cb1d0

Observation a382de76-a77c-4cf4-adc9-7778e9f7f02b · outbound

This paper cites Dynamic Spectrum Anti-Jamming Communications: Challenges and Opportunities,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Dynamic Spectrum Anti-Jamming Communications: Challenges and Opportunities,

Reference 7

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source=pdf_text observed=2026-08-02T03:27:05.023317Z digest=sha256:de521e25a4f8fe85d2ffa925746510c81f5f3bab3c52c5f68b291edd6fabad2a

Observation 77b1cf3e-a7d3-4025-97ec-d0875f0c2dc9 · outbound

This paper cites Anomaly Detection in Wireless Sensor Networks,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Anomaly Detection in Wireless Sensor Networks,

Reference 8

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source=pdf_text observed=2026-08-02T03:27:05.027195Z digest=sha256:c7d16aabb3d09645d2310f066519dafa4022f7ecc44efa5002f386f1c4e230f4

Observation a796192d-afea-45a7-9267-dcf3432b0d0a · outbound

This paper cites A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications,

Reference 9

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source=pdf_text observed=2026-08-02T03:27:05.031045Z digest=sha256:a4f715581344ebdbbe285f553456228f0a72785fe650a1ff7963643c019a4685

Observation 623aa938-0b96-4c21-8e8a-4a2a0b392bcf · outbound

This paper cites Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless Networks,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless Networks,

Reference 10

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source=pdf_text observed=2026-08-02T03:27:05.034790Z digest=sha256:427e0cb63fc09dab04837254bc5c3e3c82702746837c1f3e23f5704c3b6cc4c6

Observation 9e4a3275-90a1-4f01-b800-1594e14f4d53 · outbound

This paper cites Jamming Signals Classification Using Convolutional Neural Network,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Jamming Signals Classification Using Convolutional Neural Network,

Reference 11

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source=pdf_text observed=2026-08-02T03:27:05.038471Z digest=sha256:cd5e2f10269b1d3c5284722e6eae20169680ebee0895ed676c60bf7958c42c7a

Observation dfd233a1-36ab-4e31-97e3-69b9cd7c6eaf · outbound

This paper cites A neural network approach for wireless spectrum anomaly detection in 5G-unlicensed network,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation A neural network approach for wireless spectrum anomaly detection in 5G-unlicensed network,

Reference 12

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source=pdf_text observed=2026-08-02T03:27:05.043909Z digest=sha256:419a5e39f841446bbf5e2ff31c1bb1ce4dc343cca767a015d2f7ea025f267ad2

Observation 69a725b2-a720-41a1-912f-59fe4215ded9 · outbound

This paper cites Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features,

Reference 13

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source=pdf_text observed=2026-08-02T03:27:05.047666Z digest=sha256:8545ebcc11dd752d99af3447dd6473aeb5ab2aee9a9fd07248db28c4e18def55

Observation 0c5ed69b-9776-445a-adb5-a3a82840cb80 · outbound

This paper cites Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks,

Reference 14

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source=pdf_text observed=2026-08-02T03:27:05.051412Z digest=sha256:fed30bd5bbd33778c40d73c3ec21f1572c8393f7694502dc39057817ea1e87ff

Observation e4cfe7f9-3885-48e9-ba8c-2e59646e9ec6 · outbound

This paper cites Using Deep Convolutional Neural Network to Recognize LTE Uplink Interference,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Using Deep Convolutional Neural Network to Recognize LTE Uplink Interference,

Reference 15

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source=pdf_text observed=2026-08-02T03:27:05.055179Z digest=sha256:689f6246f8026c41ec84489939db424e8b298e471e66bc5703ec190c21ca370f

Observation a774edfb-4d18-46e2-89b9-535106f9c9a7 · outbound

This paper cites A Radio Anomaly Detection Algorithm Based on Modified Generative Adversarial Network,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation A Radio Anomaly Detection Algorithm Based on Modified Generative Adversarial Network,

Reference 16

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source=pdf_text observed=2026-08-02T03:27:05.058748Z digest=sha256:a002b47e77a725b7062fa74f413b4fffd6ac251cf0e31361e081a590917276aa

Observation d921f7b1-e11c-4b62-ad9a-9fc46d2419a5 · outbound

This paper cites Wireless Sensing in Artificial Intelligence of Things: A General Quantum Machine Learning Framework,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Wireless Sensing in Artificial Intelligence of Things: A General Quantum Machine Learning Framework,

Reference 17

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source=pdf_text observed=2026-08-02T03:27:05.062364Z digest=sha256:e7d697a12b96af2a0a5e38e36d8c326a2fa0be059c810f69881492760c7b7627

Observation 97ef23a1-6b56-4a9f-bf20-5b850617a235 · outbound

This paper cites QuaCK-TSF: Quantum- classical kernelized time series forecasting,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation QuaCK-TSF: Quantum- classical kernelized time series forecasting,

Reference 18

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source=pdf_text observed=2026-08-02T03:27:05.065968Z digest=sha256:b8cbb764988601895c5848ba37c193e2fca45886908583bc5e7b83924df64063

Observation 9199de62-c4b7-40f7-9889-158b801bc883 · outbound

This paper cites LatentQGAN: A hybrid QGAN with classical convolutional autoencoder,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation LatentQGAN: A hybrid QGAN with classical convolutional autoencoder,

Reference 19

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source=pdf_text observed=2026-08-02T03:27:05.069472Z digest=sha256:cbd1a833c1174b304ca8081df7b226ffa36a07b6130a12bbc6d685616ea38dcb

Observation 920cbd43-fb65-4a2c-aa8d-4fba3fc55d4c · outbound

This paper cites Quantum Machine Learning for Anomaly Detection: The Future of Smarter and Safer IoT Networks,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Quantum Machine Learning for Anomaly Detection: The Future of Smarter and Safer IoT Networks,

Reference 20

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source=pdf_text observed=2026-08-02T03:27:05.073121Z digest=sha256:940ce20ca3cc8e0d7c127f877df0b6fefaaf6bede8f270ac0d1eec025895efb8

Observation 44f62fa2-2860-4f68-ac22-9719611776c9 · outbound

This paper cites Learning Gaussian processes with randomized quantum local kernels,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Learning Gaussian processes with randomized quantum local kernels,

Reference 21

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source=pdf_text observed=2026-08-02T03:27:05.077026Z digest=sha256:14d9dc058856d4282ccbd47d7ccec6a123e0e3d31bb1be203f7d68afbd0f9db0

Observation efa956dd-4f9b-420e-b2eb-f155b9ea04a1 · outbound

This paper cites Multivariate time series forecasting with gate-based quantum reservoir computing on NISQ hardware,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Multivariate time series forecasting with gate-based quantum reservoir computing on NISQ hardware,

Reference 22

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source=pdf_text observed=2026-08-02T03:27:05.080648Z digest=sha256:d307e5ddd5b05343573f9c5e08ea106492ca00260a9d84a996954211005792a9

Observation ed575bb7-96e6-4b7e-b9e8-817a48e46767 · outbound

This paper cites Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers

Reference 23

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source=pdf_text observed=2026-08-02T03:27:05.084438Z digest=sha256:e2ec085eeeb04f09291ab32aa29242e5867e4682b1e58c98b09a191f8f947e3d

Observation 91236cfb-dce2-4a02-9864-87b55a3b9e87 · outbound

This paper cites Variational quantum algorithms,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Variational quantum algorithms,

Reference 24

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source=pdf_text observed=2026-08-02T03:27:05.088514Z digest=sha256:dc991152871ceb69c0db07b1a8d704d592157a8cee70a9f61a11662bdbf7c058

Observation 4b1a3026-feb4-4f91-9f60-48acd8c298cb · outbound

This paper cites A Systematic Review on Quantum Machine Learning Applications in Classification,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation A Systematic Review on Quantum Machine Learning Applications in Classification,

Reference 25

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source=pdf_text observed=2026-08-02T03:27:05.092003Z digest=sha256:c810165c912421d226f1793dac2fd98b20aafe8d35c3b232a15503b469be78c3

Observation 8692be9b-7fa5-402c-b505-847c751d9d06 · outbound

This paper cites Wireless Anomaly Signal Dataset (W ASD): An Open Dataset for Wireless Cellular Spectrum Monitoring and Anomaly Detection,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Wireless Anomaly Signal Dataset (W ASD): An Open Dataset for Wireless Cellular Spectrum Monitoring and Anomaly Detection,

Reference 26

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source=pdf_text observed=2026-08-02T03:27:05.095589Z digest=sha256:6453936db2943af9737ea4a8f82826352e2e5f7fc960fa791f261f01382cefa3

Observation bcafc9f9-ba55-41be-9ab4-45115833c3dd · outbound

This paper cites Spectrum Anomaly Detection Using Deep Neural Networks: A Wireless Signal Perspective,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Spectrum Anomaly Detection Using Deep Neural Networks: A Wireless Signal Perspective,

Reference 27

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source=pdf_text observed=2026-08-02T03:27:05.099217Z digest=sha256:ed5866b999ff359db2d0b0984ef87dc3c8f60a58477432231b0d787f6414918b

Observation 4a8debc9-bc64-48b8-ab4e-b425f0bc4c77 · outbound

This paper cites From 5G to 6G Networks: A Survey on AI-Based Jamming and Interference Detection and Mitigation,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation From 5G to 6G Networks: A Survey on AI-Based Jamming and Interference Detection and Mitigation,

Reference 28

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source=pdf_text observed=2026-08-02T03:27:05.102770Z digest=sha256:dc352a5b2f88abbd43d82614bda6ce75c7e11ab3a8a40393bfcf45d01c3034b9

Observation 1f1c9e93-1b39-49c2-a9e0-c22abbca06ac · outbound

This paper cites Low Computational Enhancement of STFT-Based Parameter Estimation,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Low Computational Enhancement of STFT-Based Parameter Estimation,

Reference 29

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source=pdf_text observed=2026-08-02T03:27:05.106557Z digest=sha256:6e96c7ea52ee208f59ab4c9859c615c7bcd9323b79654ee4d2ec676b31b40ace

Observation 5199e3bd-6811-407c-9e05-ec8056a9b6ac · outbound

This paper cites The JPEG Still Picture Compression Standard,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation The JPEG Still Picture Compression Standard,

Reference 30

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source=pdf_text observed=2026-08-02T03:27:05.110321Z digest=sha256:71bae97b786f5a18a825bfa415432db90b7a3ec6e923d7b9805e7601166a960f

Observation 440003bc-e5dd-46ff-8f00-157a68ddb0e6 · outbound

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

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Data re-uploading for a universal quantum classifier,

Reference 31

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source=pdf_text observed=2026-08-02T03:27:05.114115Z digest=sha256:de02e56c3c28077b6c04ea729e77bfcfb798091beed1de5f641949428b5afb9a

Observation f674d813-b7e1-4b89-a949-8f1872816dd2 · outbound

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

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Effect of data encoding on the expressive power of variational quantum-machine-learning models,

Reference 32

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source=pdf_text observed=2026-08-02T03:27:05.117721Z digest=sha256:22700911fbd3f3304b5ddb1452e11c84aa48ac1ea5cba90c3774f3e31b23a39b

Observation 8b3a4d62-7fb5-45ad-9423-ac7c1d892a6a · outbound

This paper cites Support-Vector Networks,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Support-Vector Networks,

Reference 33

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source=pdf_text observed=2026-08-02T03:27:05.121281Z digest=sha256:c34c2875ecf7ca9f9c02e3ca40e879b0e026fd5dc61adc286014bbfbe3f2fed2

Observation b6fb855a-15cb-4e4d-b91c-382cedad2c25 · outbound

This paper cites The Regression Analysis of Binary Sequences,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation The Regression Analysis of Binary Sequences,

Reference 34

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source=pdf_text observed=2026-08-02T03:27:05.124783Z digest=sha256:f1758fb35401f557cc6735f76923bfdc87dc98097853fe462058788f74e1d267

Observation 240f3dc6-9443-4ecf-9e8d-71904cbefb01 · outbound

This paper cites Random Features for Large-Scale Kernel Machines,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Random Features for Large-Scale Kernel Machines,

Reference 35

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source=pdf_text observed=2026-08-02T03:27:05.128353Z digest=sha256:45cc201d7e84d7555943729e5d58deb3dd10bd31e0962bb0b730274fca7514e6

Observation 5135fca7-e12a-4922-bfb9-839d9155ea93 · outbound

This paper cites Using the Nyström Method to Speed Up Kernel Machines,.

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation Using the Nyström Method to Speed Up Kernel Machines,

Reference 36

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source=pdf_text observed=2026-08-02T03:27:05.131993Z digest=sha256:2ed9d7c5322229eeec71c32f78b1f5fc4edeebf57da82c2d48faecca5aecb337

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