Paper Citation Record · LEDGER

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors

As of 13 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2411.16970.

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

pith.paper-citation-record.v1
2411.16970 v1

Coverage vector

measured 53 of 53 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: arxiv_reference, observed 2026-05-15T14:50:04.506309Z

Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation 68dd350e-292e-4fb1-8551-8c165560c227 · outbound

This paper cites A rigorous and robust quantum speed-up in supervised machine learning.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors A rigorous and robust quantum speed-up in supervised machine learning

Reference 1

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Observation 38db0994-b5d2-430f-8d9d-45b44117e56d · outbound

This paper cites A Quantum Approximate Optimization Algorithm.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors A Quantum Approximate Optimization Algorithm

Reference 2

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Observation 5253a49b-455d-47b9-add8-ea564920da89 · outbound

This paper cites Quantum machine learning.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum machine learning

Reference 3

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Observation 5571ffee-48fc-43ec-94e1-4299b9273739 · outbound

This paper cites Quantum algorithm for linear systems of equations.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum algorithm for linear systems of equations

Reference 4

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Observation e0226b57-0cfa-44a3-a9ca-06abeae0cfa4 · outbound

This paper cites Support vector machines.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Support vector machines

Reference 5

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Observation 0518e769-b672-45e6-8576-f5f76e4b2413 · outbound

This paper cites Learning with kernels: support vector machines, reg- ularization, optimization, and beyond.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Learning with kernels: support vector machines, reg- ularization, optimization, and beyond

Reference 6

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Observation b87a2396-111c-48a6-bdc8-d14b9c4525b8 · outbound

This paper cites Estimating the support of a high-dimensional distribution.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Estimating the support of a high-dimensional distribution

Reference 7

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Observation d6251d90-d33b-4dfe-984b-68c57b7b67bb · outbound

This paper cites Enhancing one-class support vector machines for unsupervised anomaly detection.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Enhancing one-class support vector machines for unsupervised anomaly detection

Reference 8

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Observation 122aa0f7-ebe5-4532-86e4-4d54d72f4560 · outbound

This paper cites One- class support vector machines approach to anomaly de- tection.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors One- class support vector machines approach to anomaly de- tection

Reference 9

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Observation 1e47eb96-1c88-40b9-b762-51fa96b1376c · outbound

This paper cites Fault detec- tion based on a robust one class support vector machine.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Fault detec- tion based on a robust one class support vector machine

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.632542Z

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Observation 908fdf53-32b5-465c-8bfc-ea7fe75f8806 · outbound

This paper cites Generalized Coherent States, Reproducing Kernels, and Quantum Support Vector Machines.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Generalized Coherent States, Reproducing Kernels, and Quantum Support Vector Machines

Reference 12

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Observation 471efd0d-405b-48d4-a277-1ae792f3f14a · outbound

This paper cites Unsupervised quantum machine learning for fraud detection.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Unsupervised quantum machine learning for fraud detection

Reference 13

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Observation bcb98359-e629-45b6-a861-2fd4c44fb782 · outbound

This paper cites Power of data in quantum ma- chine learning.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Power of data in quantum ma- chine learning

Reference 14

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Observation 945b766c-4ec8-463a-847d-ca69e76418a6 · outbound

This paper cites Exponential concentration in quantum kernel methods.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Exponential concentration in quantum kernel methods

Reference 15

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Observation f34a17cf-c9fc-41ea-9d04-b521aa5be1a8 · outbound

This paper cites Effect of alternating layered ansatzes on trainability of projected quantum kernel.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Effect of alternating layered ansatzes on trainability of projected quantum kernel

Reference 16

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Observation 560a7079-f768-4c8b-9d63-44e042aa1b49 · outbound

This paper cites On the expressivity of embedding quantum kernels.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors On the expressivity of embedding quantum kernels

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.568990Z

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Observation 4462d550-db07-4c83-893d-de822b48c764 · outbound

This paper cites Supervised quantum machine learning models are kernel methods.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Supervised quantum machine learning models are kernel methods

Reference 18

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Observation f7ed2ae5-5405-4f33-9ab1-10567b8483c2 · outbound

This paper cites Quantum machine learning beyond kernel methods.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum machine learning beyond kernel methods

Reference 19

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Observation 4a022299-1e0b-4d44-bdf8-ebbf4bff741a · outbound

This paper cites Importance of ker- nel bandwidth in quantum machine learning.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Importance of ker- nel bandwidth in quantum machine learning

Reference 20

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Observation 3a7450b7-93d6-490b-bf87-e614c9c14d0c · outbound

This paper cites Quantum machine learning in feature hilbert spaces.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum machine learning in feature hilbert spaces

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.525813Z

Source-reported events for the cited work

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Observation cabbffc3-5475-4bec-b6fb-c330706681db · outbound

This paper cites Covariant quantum kernels for data with group structure.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Covariant quantum kernels for data with group structure

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.510241Z

Source-reported events for the cited work

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Observation 262fb0b1-3660-4149-aa44-0e517ea0bb61 · outbound

This paper cites Quantum tangent kernel.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum tangent kernel

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.490289Z

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Observation 5a611c1c-8feb-4a68-8e87-aea88c9287e1 · outbound

This paper cites The complexity of quantum sup- port vector machines.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors The complexity of quantum sup- port vector machines

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.473262Z

Source-reported events for the cited work

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Observation ac304dd8-fc33-4d36-845a-733b7e668236 · outbound

This paper cites Quantum support vector machine for big data clas- sification.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum support vector machine for big data clas- sification

Reference 25

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Observation fca527e9-2d15-40af-a857-d38584faaee2 · outbound

This paper cites A hyperparameter study for quantum kernel methods.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors A hyperparameter study for quantum kernel methods

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.459380Z

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Observation eef24ed5-14b7-414f-870f-65bb2ccb219e · outbound

This paper cites Bandwidth Enables Generalization in Quantum Kernel Models.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Bandwidth Enables Generalization in Quantum Kernel Models

Reference 27

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Observation 72d37422-6700-4414-8959-1c7faf969b75 · outbound

This paper cites Quantum Kernel Methods under Scrutiny: A Benchmarking Study.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum Kernel Methods under Scrutiny: A Benchmarking Study

Reference 28

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Observation 74690b4c-0a0d-4e07-979d-db80b026ea3d · outbound

This paper cites Benchmarking quantum machine learning kernel training for classification tasks.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Benchmarking quantum machine learning kernel training for classification tasks

Reference 29

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Observation 59aa7bcb-498f-42fb-b23b-c0bdf6b8f579 · outbound

This paper cites Better than classical? The subtle art of benchmarking quantum machine learning models.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Better than classical? The subtle art of benchmarking quantum machine learning models

Reference 30

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Observation bbde91a8-48de-49c3-991d-eaca7ff696a9 · outbound

This paper cites Quantum phase recognition via quantum kernel methods.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum phase recognition via quantum kernel methods

Reference 31

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Observation 3626d1c7-2b29-4413-8c1d-368e60edf833 · outbound

This paper cites Quantum-enhanced support vector machine for sentiment classification.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum-enhanced support vector machine for sentiment classification

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.430582Z

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Observation c585e29a-88a1-4d51-a4d6-93d949dd1654 · outbound

This paper cites Brain tumour classification using quantum support vector ma- chine learning algorithm.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Brain tumour classification using quantum support vector ma- chine learning algorithm

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.413240Z

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Observation 40dd16c3-a47b-4fea-ba10-4aad3dd22fbf · outbound

This paper cites Quantum support vector machines for continuum suppression in B meson decays.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum support vector machines for continuum suppression in B meson decays

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.396372Z

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Observation 079aef92-c24a-47e2-a0ce-5efc1f7613d4 · outbound

This paper cites Evaluating Quantum Support Vector Regression Meth- ods for Price Forecasting Applications.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Evaluating Quantum Support Vector Regression Meth- ods for Price Forecasting Applications

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.382370Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6738e222-eb50-4829-a684-78249005168f · outbound

This paper cites Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.366710Z

Source-reported events for the cited work

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Observation 1fedfcfd-bf5e-411d-a150-c927ae7478f5 · outbound

This paper cites Application of quantum machine learn- ing to high energy physics analysis at LHC using quan- tum computer simulators and quantum computer hard- ware.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Application of quantum machine learn- ing to high energy physics analysis at LHC using quan- tum computer simulators and quantum computer hard- ware

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.352569Z

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Observation 4ced34cb-af34-4ad3-acce-44b8d08e631a · outbound

This paper cites Quantum anomaly detection in the latent space of proton collision events at the LHC.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum anomaly detection in the latent space of proton collision events at the LHC

Reference 38

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Observation 06b0d663-cec9-49ad-8bf8-6f69f92993a5 · outbound

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

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Machine learning of high dimensional data on a noisy quantum processor

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.338119Z

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Observation 54af8226-f257-4cc4-8c2c-c43af17bf60f · outbound

This paper cites Training quantum embedding kernels on near-term quantum computers.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Training quantum embedding kernels on near-term quantum computers

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.319357Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b718a9ee-d15b-43d8-be2e-8235078588e3 · outbound

This paper cites Support Vector Machines on Noisy Intermediate Scale Quantum Computers.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Support Vector Machines on Noisy Intermediate Scale Quantum Computers

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:46:23.759623Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 99953a5d-bec6-4f10-b967-aceb4157378f · outbound

This paper cites Quantum ma- chine learning of large datasets using randomized mea- surements.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Quantum ma- chine learning of large datasets using randomized mea- surements

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.302651Z

Source-reported events for the cited work

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Observation b9ee67b4-2607-40e9-b5a0-ccf250a81ef3 · outbound

This paper cites Experimental evaluation of quantum machine learning algorithms.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Experimental evaluation of quantum machine learning algorithms

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.276041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 60e9a62d-5db7-4d13-95cd-106618a9353a · outbound

This paper cites Credit Card Transactions Fraud Detec- tion Dataset: Simulated Credit Card Transactions gener- ated using Sparkov.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Credit Card Transactions Fraud Detec- tion Dataset: Simulated Credit Card Transactions gener- ated using Sparkov

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.252722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e80d0d7f-7c17-472b-899f-4054b5762176 · outbound

This paper cites Predicting many properties of a quantum system from very few measurements.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Predicting many properties of a quantum system from very few measurements

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.226347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation aa9460fb-6f40-4901-9af8-0bdd74ba7cd3 · outbound

This paper cites Optimizing Shadow Tomography with Generalized Measurements.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Optimizing Shadow Tomography with Generalized Measurements

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.202064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 380b702f-e9ed-40f8-b3fd-6d7c4194b7cc · outbound

This paper cites New support vector algorithms.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors New support vector algorithms

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.181459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a60d0892-1dd5-48b7-8006-8356c698168c · outbound

This paper cites LIBSVM: a li- brary for support vector machines.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors LIBSVM: a li- brary for support vector machines

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.164336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7ff8663e-e087-4a1e-bc2c-3d40831f7c40 · outbound

This paper cites Sparkov Data Generation: Generate Fake Credit Card Transaction Data, Including Fraudulent Transactions.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Sparkov Data Generation: Generate Fake Credit Card Transaction Data, Including Fraudulent Transactions

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.149087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9d2ecf22-642d-4895-b666-08ef73fa5721 · outbound

This paper cites Generalization in quantum ma- chine learning from few training data.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Generalization in quantum ma- chine learning from few training data

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.111150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b28a01f8-5385-418a-a811-ba520302fdad · outbound

This paper cites Mathematical methods of statistics.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Mathematical methods of statistics

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.085737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5487df87-d79c-4d0f-b460-23c1ab76b024 · outbound

This paper cites Note on Regression and Inheritance in the Case of Two Parents.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Note on Regression and Inheritance in the Case of Two Parents

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.058524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b21d9d98-3c82-4bb9-b311-283590a2afee · outbound

This paper cites Variable Name PCC cc number 0.000906 city population 0.000984 merch_lat 0.001136 lat 0.001278 time since first trans.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors Variable Name PCC cc number 0.000906 city population 0.000984 merch_lat 0.001136 lat 0.001278 time since first trans

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.037952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2b79bc02-4d47-42d0-954c-f8d374e1caee · outbound

This paper cites com / namebrandon / Sparkov_Data_Generation.

Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors com / namebrandon / Sparkov_Data_Generation

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:46:24.132331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation a60863d5-b955-46fe-a6c8-38c0d5b6c1fd · inbound

A Mixture-of-Experts Framework for Practical Hybrid-Quantum Models in Credit Card Fraud Detection cites this paper.

A Mixture-of-Experts Framework for Practical Hybrid-Quantum Models in Credit Card Fraud Detection Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:50:04.509196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 817ac369-4eb3-4aad-8f04-aae80a0b785c · inbound

Intelligence-Guided Adaptive Purification for DDoS-Resilient Quantum Networks: A CUDA-Q based Study cites this paper.

Intelligence-Guided Adaptive Purification for DDoS-Resilient Quantum Networks: A CUDA-Q based Study Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T08:05:52.405587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.