Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T01:37:08.033115Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2608.00053.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T01:37:08.033115Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
52 of 52 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 1faaf884-becc-4460-84e2-e9985b616e90 · outbound
Fast Trainable Multilinear Bases for Image Compression Unresolved cited work
Reference 1
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Observation 166e2683-f36b-48b9-8ae2-9f36da42ae9c · outbound
Fast Trainable Multilinear Bases for Image Compression Sullivan, Jens-Rainer Ohm, Woo-Jin Han, and Thomas Wiegand
Reference 2
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Observation 919af155-33b4-40e8-89ff-b349d66cbb65 · outbound
Fast Trainable Multilinear Bases for Image Compression Unresolved cited work
Reference 3
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Observation 43a03138-c385-42b4-830f-8423af5a8dfd · outbound
Fast Trainable Multilinear Bases for Image Compression Academic Press, 3rd edition, 2008
Reference 4
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Observation 03e917d6-6963-4315-87c0-3aebae2c9111 · outbound
Fast Trainable Multilinear Bases for Image Compression Discrete cosine transform.IEEE Trans- actions on Computers, C-23(1):90–93, 1974
Reference 5
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Observation 04c1ade3-7e37-4820-9a08-c217f1e7b575 · outbound
Fast Trainable Multilinear Bases for Image Compression An al- gorithm for the machine calculation of complex Fourier series.Mathematics of Computation, 19(90):297–301, 1965
Reference 6
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Observation 8c6a10fe-8d09-4406-a554-c57a2c239aba · outbound
Fast Trainable Multilinear Bases for Image Compression A sinusoidal family of unitary trans- forms.IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(4):356–365, 1979
Reference 7
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Observation 89d95b3e-b7ce-4c58-ac18-f4e9afa386f0 · outbound
Fast Trainable Multilinear Bases for Image Compression Lossy image compres- sion with compressive autoencoders
Reference 8
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Observation 9d2512ab-66de-488d-a220-657a26451955 · outbound
Fast Trainable Multilinear Bases for Image Compression Si- moncelli
Reference 9
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Observation 4973a255-18cc-49be-8fc4-4ccc6f589045 · outbound
Fast Trainable Multilinear Bases for Image Compression An approximate Fourier transform useful in quantum factoring
Reference 10
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Unavailable: canonical work link unavailable.
Observation 79df75b2-ffe7-4aea-b371-a29f680fff9a · outbound
Fast Trainable Multilinear Bases for Image Compression Simulating quantum computation by contracting tensor net- works.SIAM Journal on Computing, 38(3):963– 981, 2008
Reference 11
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Observation 9bc874db-3f86-4b6d-9525-e1da4cf5d906 · outbound
Fast Trainable Multilinear Bases for Image Compression Tensor-train decomposi- tion.SIAM Journal on Scientific Computing, 33(5):2295–2317, 2011
Reference 12
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Observation 779dc625-837e-4d84-91ed-ec3005613e1c · outbound
Fast Trainable Multilinear Bases for Image Compression Su- pervised learning with tensor networks
Reference 13
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Observation 3602adfa-5528-4dec-bfb0-70adcd9915bb · outbound
Fast Trainable Multilinear Bases for Image Compression Unsupervised generative model- ing using matrix product states.Physical Review X, 8(3):031012, 2018
Reference 14
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Observation 2ab159a3-f105-491e-9736-305dfb953c1f · outbound
Fast Trainable Multilinear Bases for Image Compression The theory of variational hybrid quantum-classical algorithms
Reference 15
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Unavailable: canonical work link unavailable.
Observation 83cd59ca-f5df-4372-b347-e86e61322626 · outbound
Fast Trainable Multilinear Bases for Image Compression Vari- ational quantum algorithms.Nature Reviews Physics, 3(9):625–644, 2021
Reference 16
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Unavailable: canonical work link unavailable.
Observation 092b0bad-090d-41e3-99fa-54c38536064e · outbound
Fast Trainable Multilinear Bases for Image Compression Quantum machine learning in feature Hilbert spaces.Phys- ical Review Letters, 122(4):040504, 2019
Reference 17
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Observation a65f7455-0b1f-469f-882b-1b425d229ef8 · outbound
Fast Trainable Multilinear Bases for Image Compression Parameterized quantum circuits as machine learning models.Quantum Science and Technology, 4(4):043001, 2019
Reference 18
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Observation 6db21aad-1521-4c2a-9da7-325eb1d28cc4 · outbound
Fast Trainable Multilinear Bases for Image Compression Hillar and Lek-Heng Lim
Reference 19
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Unavailable: canonical work link unavailable.
Observation 46071ea4-5eb5-44c0-ac36-fde66d7d3141 · outbound
Fast Trainable Multilinear Bases for Image Compression Training vari- ational quantum algorithms is NP-hard.Physical Review Letters, 127:120502, 2021
Reference 20
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Unavailable: canonical work link unavailable.
Observation 37af6e41-d03f-43e5-a5d1-b0bdda9bdee3 · outbound
Fast Trainable Multilinear Bases for Image Compression Rie- mannian adaptive optimization methods
Reference 21
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Unavailable: canonical work link unavailable.
Observation 89b91d17-3a52-4550-83f7-298cbb2b70da · outbound
Fast Trainable Multilinear Bases for Image Compression Riemannian optimization of isomet- ric tensor networks.SciPost Physics, 10(2):040, 2021
Reference 22
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Observation 83f2ffbf-1a0a-4265-b9c6-8e07648cdb64 · outbound
Fast Trainable Multilinear Bases for Image Compression NTIRE 2017 challenge on single image super-resolution: Dataset and study
Reference 23
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Unavailable: canonical work link unavailable.
Observation cc2156ee-b820-45ac-9fa6-6889d7b66c70 · outbound
Fast Trainable Multilinear Bases for Image Compression Quick, draw! dataset.https:// quickdraw.withgoogle.com/data, 2017
Reference 24
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Unavailable: canonical work link unavailable.
Observation 3083532f-ba58-4214-a72b-a28a5c6a9984 · outbound
Fast Trainable Multilinear Bases for Image Compression A neural representa- tion of sketch drawings
Reference 25
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Unavailable: canonical work link unavailable.
Observation cfc4012d-eea5-4023-b018-a6ad0feb9740 · outbound
Fast Trainable Multilinear Bases for Image Compression Arias, and Steven T
Reference 26
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Observation 0b4f2ccf-a128-4b47-b2d3-db3abd001224 · outbound
Fast Trainable Multilinear Bases for Image Compression Princeton University Press, 2008
Reference 27
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Observation 5c9eb376-3c1d-4cd1-a30f-e776eed1c798 · outbound
Fast Trainable Multilinear Bases for Image Compression Efficient simulation of one- dimensional quantum many-body systems.Phys- ical Review Letters, 93(4):040502, 2004
Reference 28
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Observation 65d56de8-372a-4968-b9dd-1e96097d91d0 · outbound
Fast Trainable Multilinear Bases for Image Compression Entanglement renormalization
Reference 29
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Observation cc394f31-3397-4db6-abb3-6daa2d544e91 · outbound
Fast Trainable Multilinear Bases for Image Compression Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Reference 30
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Observation 8c05fedb-b3d3-43eb-ab9c-002406602613 · outbound
Fast Trainable Multilinear Bases for Image Compression Categor- ical reparameterization with Gumbel-Softmax
Reference 31
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Observation b4b20b32-720e-4e4d-9344-2e785f2fce14 · outbound
Fast Trainable Multilinear Bases for Image Compression Reparam- eterizable subset sampling via continuous relax- ations
Reference 32
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Observation 5e042915-cea6-4e23-bf3e-a67e3d9a330c · outbound
Fast Trainable Multilinear Bases for Image Compression A feasible method for optimization with orthogonality constraints
Reference 33
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Observation 1468162b-252f-46fd-bb44-040b9324a23b · outbound
Fast Trainable Multilinear Bases for Image Compression Cambridge University Press, 2023
Reference 34
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Observation 95c984dd-2f3e-4399-ab0e-bc6d5c503540 · outbound
Fast Trainable Multilinear Bases for Image Compression Kingma and Jimmy Ba
Reference 35
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Observation 4194eeeb-4300-40d8-b432-ee65b8f0c874 · outbound
Fast Trainable Multilinear Bases for Image Compression Riemannian adaptive stochastic gradient algorithms on matrix manifolds
Reference 36
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Observation da3407bb-bcba-4092-8e80-bddffe733664 · outbound
Fast Trainable Multilinear Bases for Image Compression McClean, Sergio Boixo, Vadim N
Reference 37
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Observation 83077ced-28b9-48e4-a7be-dd40430fa8de · outbound
Fast Trainable Multilinear Bases for Image Compression Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, and Patrick J
Reference 38
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Observation 2466e106-a9b0-43a7-85c1-5ae5d4ee3c7b · outbound
Fast Trainable Multilinear Bases for Image Compression Yip, and K
Reference 39
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Observation 5eb715ea-078f-4c27-b47f-6c9421947652 · outbound
Fast Trainable Multilinear Bases for Image Compression Tropical tensor network for ground states of spin glasses
Reference 40
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Observation 0e639bfc-4398-474a-b651-86e7d3b122f2 · outbound
Fast Trainable Multilinear Bases for Image Compression Computing solu- tion space properties of combinatorial optimiza- tion problems via generic tensor networks.SIAM Journal on Scientific Computing, 45(3):A1239– A1270, 2023
Reference 41
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Observation 06e511e0-a31f-486b-8423-366e74d20031 · outbound
Fast Trainable Multilinear Bases for Image Compression Fast and numerically stable algorithms for discrete cosine transforms.Linear Algebra and its Applications, 394:309–345, 2005
Reference 42
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Observation d9654847-3eed-4480-ae6d-5acf3753bc9b · outbound
Fast Trainable Multilinear Bases for Image Compression Unresolved cited work
Reference 43
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Observation a82d94ef-5a42-4b11-8e4d-1c21f66d6e5e · outbound
Fast Trainable Multilinear Bases for Image Compression Harrison Smith, and S
Reference 44
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Observation 75370111-1d7a-4c15-a366-ad3f84916b5b · outbound
Fast Trainable Multilinear Bases for Image Compression Moschytz
Reference 45
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Observation e00263b0-171a-4ae3-acbb-e26f58b4b7f3 · outbound
Fast Trainable Multilinear Bases for Image Compression Fast algo- rithms for the discrete cosine transform.IEEE Transactions on Signal Processing, 40(9):2174– 2193, 1992
Reference 46
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Observation 257e04d4-c717-4a54-add0-b08bb5bbec89 · outbound
Fast Trainable Multilinear Bases for Image Compression Suboptimality of the Karhunen–Lo` eve transform for transform coding.IEEE Transac- tions on Information Theory, 50(8):1605–1619, 2004
Reference 47
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Observation 19486763-dec0-448e-bf17-3f016aee6c7d · outbound
Fast Trainable Multilinear Bases for Image Compression JAX: composable transformations of Python+NumPy programs.http://github
Reference 48
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Observation 0e9e83b0-52df-492e-a456-eed385a99ed8 · outbound
Fast Trainable Multilinear Bases for Image Compression Differentiable programming tensor net- works.Physical Review X, 9:031041, 2019
Reference 49
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Observation 5ec65ec4-61b7-4476-96c3-e537dd001915 · outbound
Fast Trainable Multilinear Bases for Image Compression Prob- abilistic inference in the era of tensor networks and differential programming.Physical Review Research, 6:033261, 2024
Reference 50
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Observation c776c5ff-5217-4b4e-b4cd-d4bdf56515f7 · outbound
Fast Trainable Multilinear Bases for Image Compression How to generate ran- dom matrices from the classical compact groups
Reference 51
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Observation e555dc15-c2d2-41fd-a635-aec9045c7a09 · outbound
Fast Trainable Multilinear Bases for Image Compression OnlyO(2)is disconnected, splitting intodet = +1 rotations anddet =−1reflections
Reference 52
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No inbound Pith citation observations are available.