New perspectives on quantum kernels through the lens of entangled tensor kernels | Paper Citation Record

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This paper cites (20) In particular, we see from Eq.

New perspectives on quantum kernels through the lens of entangled tensor kernels (20) In particular, we see from Eq

Reference 1

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This paper cites In particular, one can notice that here the eigenfunctions 6 and eigenvalues of the product kernel are simply the products of those of the individual kernels.

New perspectives on quantum kernels through the lens of entangled tensor kernels In particular, one can notice that here the eigenfunctions 6 and eigenvalues of the product kernel are simply the products of those of the individual kernels

Reference 2

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New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 3

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This paper cites kernel trick.

New perspectives on quantum kernels through the lens of entangled tensor kernels kernel trick

Reference 5

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This paper cites This requires O(dN ) multiplications – i.e.

New perspectives on quantum kernels through the lens of entangled tensor kernels This requires O(dN ) multiplications – i.e

Reference 6

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This paper cites Finally, take the product of all con- stituent kernel evaluations.

New perspectives on quantum kernels through the lens of entangled tensor kernels Finally, take the product of all con- stituent kernel evaluations

Reference 7

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This paper cites en- tangled.

New perspectives on quantum kernels through the lens of entangled tensor kernels en- tangled

Reference 8

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Reference 10

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This paper cites We discuss the potential and limitations in this regard in Section V C.

New perspectives on quantum kernels through the lens of entangled tensor kernels We discuss the potential and limitations in this regard in Section V C

Reference 11

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This paper cites super- polynomial bond-dimension.

New perspectives on quantum kernels through the lens of entangled tensor kernels super- polynomial bond-dimension

Reference 13

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This paper cites One ﬁnal important remark is that the above conditions are only necessary (but not suﬃcient) for useful quantum kernels.

New perspectives on quantum kernels through the lens of entangled tensor kernels One ﬁnal important remark is that the above conditions are only necessary (but not suﬃcient) for useful quantum kernels

Reference 17

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Reference 18

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New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 19

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This paper cites We leave further study of these approaches to dequanti- zation of classical kernel methods to future work, however we make a few remarks.

New perspectives on quantum kernels through the lens of entangled tensor kernels We leave further study of these approaches to dequanti- zation of classical kernel methods to future work, however we make a few remarks

Reference 20

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This paper cites Note that these are diﬀerent from the eigenspectra of unitaries or quantum states themselves.

New perspectives on quantum kernels through the lens of entangled tensor kernels Note that these are diﬀerent from the eigenspectra of unitaries or quantum states themselves

Reference 21

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This paper cites no free lunch.

New perspectives on quantum kernels through the lens of entangled tensor kernels no free lunch

Reference 22

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This paper cites Supervised learning with quantum comput- ers.

New perspectives on quantum kernels through the lens of entangled tensor kernels Supervised learning with quantum comput- ers

Reference 23

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This paper cites Machine learning & artiﬁcial intelligence in the quantum domain: a review of recent progress.

New perspectives on quantum kernels through the lens of entangled tensor kernels Machine learning & artiﬁcial intelligence in the quantum domain: a review of recent progress

Reference 24

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This paper cites Variational quantum algorithms.

New perspectives on quantum kernels through the lens of entangled tensor kernels Variational quantum algorithms

Reference 25

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This paper cites Parameterized quantum circuits as machine learning models.

New perspectives on quantum kernels through the lens of entangled tensor kernels Parameterized quantum circuits as machine learning models

Reference 26

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This paper cites Learning with kernels: support vector ma- chines, regularization, optimization, and beyond.

New perspectives on quantum kernels through the lens of entangled tensor kernels Learning with kernels: support vector ma- chines, regularization, optimization, and beyond

Reference 27

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This paper cites Support vector machines.

New perspectives on quantum kernels through the lens of entangled tensor kernels Support vector machines

Reference 28

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This paper cites Kernel methods in quantum machine learning.

New perspectives on quantum kernels through the lens of entangled tensor kernels Kernel methods in quantum machine learning

Reference 29

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This paper cites & Killoran, N.

New perspectives on quantum kernels through the lens of entangled tensor kernels & Killoran, N

Reference 30

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This paper cites Córcoles, Kristan Temme, Aram W.

New perspectives on quantum kernels through the lens of entangled tensor kernels Córcoles, Kristan Temme, Aram W

Reference 31

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This paper cites doi:10.1038/s41586-019-0980-2.

New perspectives on quantum kernels through the lens of entangled tensor kernels doi:10.1038/s41586-019-0980-2

Reference 32

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

New perspectives on quantum kernels through the lens of entangled tensor kernels Training quantum embedding kernels on near-term quantum computers

Reference 33

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This paper cites On the expressivity of embedding quantum kernels.

New perspectives on quantum kernels through the lens of entangled tensor kernels On the expressivity of embedding quantum kernels

Reference 34

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This paper cites doi:10.1088/2632-2153/ad2f51.

New perspectives on quantum kernels through the lens of entangled tensor kernels doi:10.1088/2632-2153/ad2f51

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This paper cites A Unified Framework for Trace-induced Quantum Kernels.

New perspectives on quantum kernels through the lens of entangled tensor kernels A Unified Framework for Trace-induced Quantum Kernels

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

New perspectives on quantum kernels through the lens of entangled tensor kernels A rigorous and robust quantum speed-up in su- pervised machine learning

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This paper cites The Inductive Bias of Quantum Kernels.

New perspectives on quantum kernels through the lens of entangled tensor kernels The Inductive Bias of Quantum Kernels

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This paper cites Power of data in quantum machine learn- ing.

New perspectives on quantum kernels through the lens of entangled tensor kernels Power of data in quantum machine learn- ing

Reference 39

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This paper cites Exponential concentration in quantum kernel methods.

New perspectives on quantum kernels through the lens of entangled tensor kernels Exponential concentration in quantum kernel methods

Reference 40

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New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 41

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This paper cites Importance of kernel bandwidth in quantum machine learning.

New perspectives on quantum kernels through the lens of entangled tensor kernels Importance of kernel bandwidth in quantum machine learning

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This paper cites Wild, and Ruslan Shaydulin.

New perspectives on quantum kernels through the lens of entangled tensor kernels Wild, and Ruslan Shaydulin

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This paper cites Neu- ral quantum kernels: Training quantum kernels with quantum neural networks.

New perspectives on quantum kernels through the lens of entangled tensor kernels Neu- ral quantum kernels: Training quantum kernels with quantum neural networks

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This paper cites Tensor net- works for dimensionality reduction and large-scale opti- mization: Part 1 low-rank tensor decompositions.

New perspectives on quantum kernels through the lens of entangled tensor kernels Tensor net- works for dimensionality reduction and large-scale opti- mization: Part 1 low-rank tensor decompositions

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This paper cites Tensor networks in machine learning.

New perspectives on quantum kernels through the lens of entangled tensor kernels Tensor networks in machine learning

Reference 46

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This paper cites Tensor networks in machine learning.

New perspectives on quantum kernels through the lens of entangled tensor kernels Tensor networks in machine learning

Reference 47

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This paper cites Tensor decom- positions for learning latent variable models.

New perspectives on quantum kernels through the lens of entangled tensor kernels Tensor decom- positions for learning latent variable models

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This paper cites Expressive power of tensor-network factorizations for probabilistic modeling.

New perspectives on quantum kernels through the lens of entangled tensor kernels Expressive power of tensor-network factorizations for probabilistic modeling

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This paper cites Potential and limitations of random fourier features for dequantizing quantum machine learning.

New perspectives on quantum kernels through the lens of entangled tensor kernels Potential and limitations of random fourier features for dequantizing quantum machine learning

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This paper cites Schollw \"o ck ,\ 10.1016/j.aop.2010.09.012 journal journal Ann.

New perspectives on quantum kernels through the lens of entangled tensor kernels Schollw \"o ck ,\ 10.1016/j.aop.2010.09.012 journal journal Ann

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This paper cites Hand- waving and interpretive dance: an introductory course on tensor networks.

New perspectives on quantum kernels through the lens of entangled tensor kernels Hand- waving and interpretive dance: an introductory course on tensor networks

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This paper cites URL http://dx.

New perspectives on quantum kernels through the lens of entangled tensor kernels URL http://dx

Reference 53

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This paper cites On kernel-target alignment.

New perspectives on quantum kernels through the lens of entangled tensor kernels On kernel-target alignment

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Observation 52086c16-8a97-4ed8-923a-f36eace9d319 · outbound

This paper cites Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks.Nature Communications, 12(1):2914, May 2021.

New perspectives on quantum kernels through the lens of entangled tensor kernels Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks.Nature Communications, 12(1):2914, May 2021

Reference 55

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.540640Z

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Observation 666133b8-a27a-4a00-83b9-aa8087943ff4 · outbound

This paper cites Shot-frugal and Robust quantum kernel classifiers.

New perspectives on quantum kernels through the lens of entangled tensor kernels Shot-frugal and Robust quantum kernel classifiers

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:22:11.672108Z

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Observation 92024e57-5efc-4a29-a60c-9f97894d3bbd · outbound

This paper cites Quantum kernel methods under scrutiny: a benchmarking study.

New perspectives on quantum kernels through the lens of entangled tensor kernels Quantum kernel methods under scrutiny: a benchmarking study

Reference 57

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.617308Z

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Observation 19bddb57-4b27-4231-9fb1-5f4bf7285c49 · outbound

This paper cites Wainwright.

New perspectives on quantum kernels through the lens of entangled tensor kernels Wainwright

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.512173Z

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Observation f76bf1fb-8a4d-441e-8367-ce7d844bd96d · outbound

This paper cites Matrix- product operators and states: Np-hardness and undecid- ability.

New perspectives on quantum kernels through the lens of entangled tensor kernels Matrix- product operators and states: Np-hardness and undecid- ability

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.405555Z

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Observation ed24df98-da56-49dd-a4e9-1d68e283cdb2 · outbound

This paper cites Werner, D.

New perspectives on quantum kernels through the lens of entangled tensor kernels Werner, D

Reference 60

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.568745Z

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Observation 92cdcf8e-1271-4575-bcd0-874b9475480e · outbound

This paper cites Puriﬁcations of multipar- tite states: limitations and constructive methods.

New perspectives on quantum kernels through the lens of entangled tensor kernels Puriﬁcations of multipar- tite states: limitations and constructive methods

Reference 61

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.598457Z

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Observation 330cd1ff-60b9-4295-ba5a-479cdc5c0642 · outbound

This paper cites Vartiainen, Mikko Möttönen, and Martti M.

New perspectives on quantum kernels through the lens of entangled tensor kernels Vartiainen, Mikko Möttönen, and Martti M

Reference 62

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.622520Z

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Observation f2801442-0722-45f7-a2e5-6a8e3fa7cd81 · outbound

This paper cites Dequantizing algorithms to understand quantum advantage in machine learning.

New perspectives on quantum kernels through the lens of entangled tensor kernels Dequantizing algorithms to understand quantum advantage in machine learning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.397132Z

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Observation 2975de23-829a-44a7-934b-30658bb0cd3d · outbound

This paper cites Schreiber, Jens Eisert, and Johannes Jakob Meyer.

New perspectives on quantum kernels through the lens of entangled tensor kernels Schreiber, Jens Eisert, and Johannes Jakob Meyer

Reference 64

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.637399Z

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Observation d2f8b9ff-3ed0-49de-9982-73fa0dc217ba · outbound

This paper cites Classically approximat- ing variational quantum machine learning with random fourier features.

New perspectives on quantum kernels through the lens of entangled tensor kernels Classically approximat- ing variational quantum machine learning with random fourier features

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.413244Z

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Observation 047571e4-3da3-43b6-9481-96b933b49f00 · outbound

This paper cites Jordan and Pawel Wocjan.

New perspectives on quantum kernels through the lens of entangled tensor kernels Jordan and Pawel Wocjan

Reference 66

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.578287Z

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Observation 34a06380-c87e-4102-bb40-cba5f2d3e041 · outbound

This paper cites On verifiable quantum advantage with peaked circuit sampling.

New perspectives on quantum kernels through the lens of entangled tensor kernels On verifiable quantum advantage with peaked circuit sampling

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:22:11.691858Z

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Observation 80061662-32bf-497e-8c65-043056659db1 · outbound

This paper cites The effect of data encoding on the expressive power of variational quantum machine learning models.

New perspectives on quantum kernels through the lens of entangled tensor kernels The effect of data encoding on the expressive power of variational quantum machine learning models

Reference 68

Resolution: verified exact; doi, observed 2026-05-22T22:22:11.583937Z

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Observation 2ec9a060-d2e7-48cf-85d9-49ba5c194d14 · outbound

This paper cites (A1) One can immediately see that K(N,c)(x, x′) = NY Kc(x, x′), (A2) where Kc(x, x′) = c + x⊤x′.

New perspectives on quantum kernels through the lens of entangled tensor kernels (A1) One can immediately see that K(N,c)(x, x′) = NY Kc(x, x′), (A2) where Kc(x, x′) = c + x⊤x′

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.424056Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 410afe93-c24a-4e00-9e8c-4feece585b87 · outbound

This paper cites K(N,a)(x, x′) := NX i=1 aiKi(x, x′) (A7) is a valid kernel.

New perspectives on quantum kernels through the lens of entangled tensor kernels K(N,a)(x, x′) := NX i=1 aiKi(x, x′) (A7) is a valid kernel

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.541000Z

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Observation a4ac8c79-a020-4c23-97cd-0b079bc20b81 · outbound

This paper cites standard form.

New perspectives on quantum kernels through the lens of entangled tensor kernels standard form

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.436252Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2dfcca41-b8e1-4586-903a-3d8763ebb4c4 · outbound

This paper cites We stress that as the subspace in which the rotation occurs is ﬁxed, the order and position of the CNOT gates and single qubit gates are also ﬁxed – i.e.

New perspectives on quantum kernels through the lens of entangled tensor kernels We stress that as the subspace in which the rotation occurs is ﬁxed, the order and position of the CNOT gates and single qubit gates are also ﬁxed – i.e

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T22:22:12.534046Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6c925c4a-5588-4710-b885-69f44a2045a2 · outbound

This paper cites an unresolved cited work.

New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-05-22T22:22:12.401075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 15ee34e1-8143-4b68-b89f-7f1f8d08445d · outbound

This paper cites an unresolved cited work.

New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-05-22T22:22:12.420388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 96fc40f8-3fb7-422c-9679-d905dc602381 · outbound

This paper cites an unresolved cited work.

New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-05-22T22:22:12.447083Z

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Observation f045c4f9-9a35-4efb-a712-c0fe86c37e93 · outbound

This paper cites an unresolved cited work.

New perspectives on quantum kernels through the lens of entangled tensor kernels Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-05-22T22:22:12.551713Z

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