Efficient upsampling for tensor-network and quantum-state encoded functions | Paper Citation Record

Observation 582ae093-910e-47b6-bf3b-80c8e64a4dfa · outbound

This paper cites Since the function is highly oscillatory, accurate interpola- tion requires at least two samples per period.

Efficient upsampling for tensor-network and quantum-state encoded functions Since the function is highly oscillatory, accurate interpola- tion requires at least two samples per period

Reference 1

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 2

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Observation 1a018d1d-2fbb-42c2-8717-b382547ec5e4 · outbound

This paper cites Although Per- lin’s noise is widely used in the literature (see App.

Efficient upsampling for tensor-network and quantum-state encoded functions Although Per- lin’s noise is widely used in the literature (see App

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Efficient upsampling for tensor-network and quantum-state encoded functions Schafer and L

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This paper cites Wang, in2022 2nd International Conference on Computer Graphics, Image and Virtualization (IC- CGIV)(IEEE, 2022) p.

Efficient upsampling for tensor-network and quantum-state encoded functions Wang, in2022 2nd International Conference on Computer Graphics, Image and Virtualization (IC- CGIV)(IEEE, 2022) p

Reference 6

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Observation 35fb1014-c358-4510-9713-c2f6bd43612f · outbound

This paper cites Lagae, S.

Efficient upsampling for tensor-network and quantum-state encoded functions Lagae, S

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Observation bb9425d5-1879-446d-bf4e-1e1fb0e404b6 · outbound

This paper cites Perlin, ACM SIGGRAPH Computer Graphics 19, 287–296 (1985).

Efficient upsampling for tensor-network and quantum-state encoded functions Perlin, ACM SIGGRAPH Computer Graphics 19, 287–296 (1985)

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Observation a7e042f6-5e81-4b71-b1a0-a59809e48be4 · outbound

This paper cites Hagstrom and D.

Efficient upsampling for tensor-network and quantum-state encoded functions Hagstrom and D

Reference 10

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Observation 360531bb-8cdf-4cf8-8aff-212440b7d69a · outbound

This paper cites Keys, IEEE Transactions on Acoustics, Speech, and Signal Processing29, 1153–1160 (1981).

Efficient upsampling for tensor-network and quantum-state encoded functions Keys, IEEE Transactions on Acoustics, Speech, and Signal Processing29, 1153–1160 (1981)

Reference 12

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This paper cites Saupe, Algorithms for random fractals, inThe Science of Fractal Images(Springer New York,.

Efficient upsampling for tensor-network and quantum-state encoded functions Saupe, Algorithms for random fractals, inThe Science of Fractal Images(Springer New York,

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This paper cites Fournier, D.

Efficient upsampling for tensor-network and quantum-state encoded functions Fournier, D

Reference 15

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This paper cites Perlin, ACM Transactions on Graphics21, 681–682 (2002).

Efficient upsampling for tensor-network and quantum-state encoded functions Perlin, ACM Transactions on Graphics21, 681–682 (2002)

Reference 16

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This paper cites Leland, M.

Efficient upsampling for tensor-network and quantum-state encoded functions Leland, M

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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This paper cites Jilesen, J.

Efficient upsampling for tensor-network and quantum-state encoded functions Jilesen, J

Reference 21

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 22

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 23

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 25

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Efficient upsampling for tensor-network and quantum-state encoded functions Ryzhakov and I

Reference 26

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This paper cites Tensor Numerical Methods for High-dimensional PDEs: Basic Theory and Initial Applications.

Efficient upsampling for tensor-network and quantum-state encoded functions Tensor Numerical Methods for High-dimensional PDEs: Basic Theory and Initial Applications

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Efficient upsampling for tensor-network and quantum-state encoded functions Kazeev and C

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 30

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This paper cites QTT-isogeometric solver in two dimensions.

Efficient upsampling for tensor-network and quantum-state encoded functions QTT-isogeometric solver in two dimensions

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This paper cites Quantum-Inspired Solver for Simulating Material Deformations.

Efficient upsampling for tensor-network and quantum-state encoded functions Quantum-Inspired Solver for Simulating Material Deformations

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Efficient upsampling for tensor-network and quantum-state encoded functions Gourianov, M

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Efficient upsampling for tensor-network and quantum-state encoded functions Pisoni, R

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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This paper cites Multiscale interpolative construction of quantized tensor trains.

Efficient upsampling for tensor-network and quantum-state encoded functions Multiscale interpolative construction of quantized tensor trains

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Efficient upsampling for tensor-network and quantum-state encoded functions Lubasch, P

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Efficient upsampling for tensor-network and quantum-state encoded functions Piecewise Polynomial Tensor Network Quantum Feature Encoding

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Efficient upsampling for tensor-network and quantum-state encoded functions Oseledets and E

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Efficient upsampling for tensor-network and quantum-state encoded functions Savostyanov and I

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Efficient upsampling for tensor-network and quantum-state encoded functions Núñez Fernández, M

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Efficient upsampling for tensor-network and quantum-state encoded functions Tindall, M

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Ye and N

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Efficient upsampling for tensor-network and quantum-state encoded functions De Lathauwer, B

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Efficient upsampling for tensor-network and quantum-state encoded functions Thevenaz, T

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Efficient upsampling for tensor-network and quantum-state encoded functions Stoer, R

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Chertkov, G

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Efficient upsampling for tensor-network and quantum-state encoded functions Ion, torchtt, https://github.com/ion-g-ion/ torchTT(2026)

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Efficient upsampling for tensor-network and quantum-state encoded functions Coarse-To-Fine Tensor Trains for Compact Visual Representations

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Efficient upsampling for tensor-network and quantum-state encoded functions Shi and A

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Efficient upsampling for tensor-network and quantum-state encoded functions Dolgov and B

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Efficient upsampling for tensor-network and quantum-state encoded functions Chepiga and S

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Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

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Efficient upsampling for tensor-network and quantum-state encoded functions Fournier, D

Reference 64

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This paper cites In TT form, we introduce core tensors Gk ∈ Rrk−1×nk×rk , k = 1 ,.

Efficient upsampling for tensor-network and quantum-state encoded functions In TT form, we introduce core tensors Gk ∈ Rrk−1×nk×rk , k = 1 ,

Reference 65

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Efficient upsampling for tensor-network and quantum-state encoded functions Let the points be uniform distributed xi = i 2N , i = 0, 1,

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Efficient upsampling for tensor-network and quantum-state encoded functions Let A ∈ Rn1×n2×···×nd be a d-way tensor

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Observation 4ca4f7ca-15f6-4799-9131-b693129d660d · outbound

This paper cites Reshaping {M (xi)}2N −1 i=0 into the N-way tensor Ma1···aN yields Ma1···aN = G1(a1) G2(a2) · · ·GN (aN ).

Efficient upsampling for tensor-network and quantum-state encoded functions Reshaping {M (xi)}2N −1 i=0 into the N-way tensor Ma1···aN yields Ma1···aN = G1(a1) G2(a2) · · ·GN (aN )

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.890425Z

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Observation 15872013-502f-4f44-85c8-3fb42b5d20bd · outbound

This paper cites For k∈ 12 {0,.

Efficient upsampling for tensor-network and quantum-state encoded functions For k∈ 12 {0,

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.898130Z

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Observation 5c48ff31-3628-4527-a33f-7e1f58d94996 · outbound

This paper cites The first method has a convergence error rate ofO(h3), whereas the second has a rate ofO(h2), wherehis the grid size.

Efficient upsampling for tensor-network and quantum-state encoded functions The first method has a convergence error rate ofO(h3), whereas the second has a rate ofO(h2), wherehis the grid size

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.905866Z

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Observation 279701ec-cadc-4f1f-84ae-8070299be428 · outbound

This paper cites , xi+⌈m/2⌉} and forming the unique degree-m polynomial that passes through those values.

Efficient upsampling for tensor-network and quantum-state encoded functions , xi+⌈m/2⌉} and forming the unique degree-m polynomial that passes through those values

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.914756Z

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Unavailable: canonical work link unavailable.

Observation 14a51254-96ed-4d0d-bef7-e4d922be1e7c · outbound

This paper cites cardinal.

Efficient upsampling for tensor-network and quantum-state encoded functions cardinal

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.920342Z

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Observation 9a557c65-bd4e-40e2-ad74-ca6b60af1434 · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.925757Z

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Observation de0ef801-063a-4cc2-988e-900ee029d9cc · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.931497Z

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Unavailable: canonical work link unavailable.

Observation db3b3639-cdc6-496d-a2f9-a4e40a881a26 · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.938020Z

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Observation 00c394f3-4b60-4367-8fe3-f8a82990d57c · outbound

This paper cites For each segment endpoint pair at indicesi and i + d, compute the midpoint indexm = i + d/2.

Efficient upsampling for tensor-network and quantum-state encoded functions For each segment endpoint pair at indicesi and i + d, compute the midpoint indexm = i + d/2

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.944524Z

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Observation 07df9dab-f010-4a2b-8781-4c8637d88af1 · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.951050Z

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Observation 9c56496e-802e-4d53-b1b8-b0bff688acbd · outbound

This paper cites The final profile{H[0], H[1],.

Efficient upsampling for tensor-network and quantum-state encoded functions The final profile{H[0], H[1],

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.960433Z

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Observation 85027da2-43fd-452c-8e83-516fc6f58c7e · outbound

This paper cites For a real coordinate x, set i0 = ⌊x⌋ and t = x−i 0.

Efficient upsampling for tensor-network and quantum-state encoded functions For a real coordinate x, set i0 = ⌊x⌋ and t = x−i 0

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.966988Z

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Observation f47e4dd3-6907-47f9-a06c-d1a7bd71c985 · outbound

This paper cites color- ing.

Efficient upsampling for tensor-network and quantum-state encoded functions color- ing

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.975393Z

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Unavailable: canonical work link unavailable.

Observation 5202725b-634c-49fe-8158-3d00aaefa8f9 · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.983892Z

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Observation 6ec4633e-e51b-4422-b990-50d0f3057a9a · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:28.990924Z

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Unavailable: canonical work link unavailable.

Observation 84f5dd15-4161-40b0-ad1a-b8314cbbd837 · outbound

This paper cites an unresolved cited work.

Efficient upsampling for tensor-network and quantum-state encoded functions Unresolved cited work

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:29.008711Z

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Observation b632c610-7013-4289-94e3-716438c2ebe4 · outbound

This paper cites Showcasing Perlin noise and the midpoint algorithm 8 10 12 14 16 18 20 No.

Efficient upsampling for tensor-network and quantum-state encoded functions Showcasing Perlin noise and the midpoint algorithm 8 10 12 14 16 18 20 No

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-03T12:17:29.030863Z

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