Paper Citation Record · LEDGER

Randomized algorithms for streaming low-rank approximation in tree tensor network format

As of 23 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.06111.

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

pith.paper-citation-record.v1
2412.06111 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

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measured 43 of 43 standing notices

One-hop event checks from named stored sources.

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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

43 of 43 outbound references displayed

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verified fuzzy34
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2a35a9ed-1e29-412a-ae54-61f7f5476580 · outbound

This paper cites Kolda and Brett W.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Kolda and Brett W

Reference 1

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Observation 231ccb9d-17af-466a-b124-22f8031d28b3 · outbound

This paper cites Oseledets.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Oseledets

Reference 2

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Observation 26bd0e73-c5bb-4eb3-98f0-cf1ba6c0d2cb · outbound

This paper cites Hierarchical singular value decomposi tion of tensors.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Hierarchical singular value decomposi tion of tensors

Reference 3

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Observation e0f84e0f-0b25-4bde-a7cc-2c81241c640a · outbound

This paper cites Classical sim ulation of quantum many-body systems with a tree tensor network.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Classical sim ulation of quantum many-body systems with a tree tensor network

Reference 4

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Observation 3eb233e5-9240-4369-a58b-d5e3d1351de5 · outbound

This paper cites Simulating strongly correlated quantum systems with tree tensor networks.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Simulating strongly correlated quantum systems with tree tensor networks

Reference 5

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Observation f4bb427d-7ba2-4c0c-8054-0165e60866d8 · outbound

This paper cites Tree tensor network state with variable tensor order: An eﬃcient multir eference method for strongly correlated systems.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Tree tensor network state with variable tensor order: An eﬃcient multir eference method for strongly correlated systems

Reference 6

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Observation 3d13fe1e-d02d-4d58-8615-fbd381dfc3cf · outbound

This paper cites Ti me integration of tree tensor net- works.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Ti me integration of tree tensor net- works

Reference 7

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Observation e77fca68-82ed-4321-8308-6a0caf6b71e5 · outbound

This paper cites Ra nk-adaptive time integration of tree tensor networks.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Ra nk-adaptive time integration of tree tensor networks

Reference 8

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This paper cites Griﬃths singularities in the ran- dom quantum Ising antiferromagnet: A tree tensor network re normalization group study.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Griﬃths singularities in the ran- dom quantum Ising antiferromagnet: A tree tensor network re normalization group study

Reference 9

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Observation 45b6fe2c-b5c8-40fb-aa95-98c9d19aeb65 · outbound

This paper cites Tree tensor network approach to sim ulating Shor’s algorithm.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Tree tensor network approach to sim ulating Shor’s algorithm

Reference 10

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Observation 2e4f992a-ae01-40a0-8237-dda07d0f696e · outbound

This paper cites Tree tens or networks for generative modeling.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Tree tens or networks for generative modeling

Reference 11

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Observation d7d420f2-0e12-4d02-9154-c3cf4d334671 · outbound

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Randomized algorithms for streaming low-rank approximation in tree tensor network format Unresolved cited work

Reference 12

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Observation 8efe46f8-0913-442c-b575-3634e11c6520 · outbound

This paper cites A multilinear singular value decomposition.

Randomized algorithms for streaming low-rank approximation in tree tensor network format A multilinear singular value decomposition

Reference 13

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Observation 474892c7-79e4-4fbe-bcf8-4f8f173372d5 · outbound

This paper cites A new truncation strategy for the higher-order singular value decomposition.

Randomized algorithms for streaming low-rank approximation in tree tensor network format A new truncation strategy for the higher-order singular value decomposition

Reference 14

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Observation 3ee49f8f-1901-46f7-86c4-f04d849632e0 · outbound

This paper cites Saibaba, and Misha E.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Saibaba, and Misha E

Reference 15

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Observation ab7fae04-753c-40e6-b7e2-b8a21e46d0a0 · outbound

This paper cites Randomized algorithms for the approximations of Tucker and the tensor train decompositions.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Randomized algorithms for the approximations of Tucker and the tensor train decompositions

Reference 16

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Observation 26fab354-6110-48bb-b5b7-4ca864d0bd86 · outbound

This paper cites Reid, and Arvind K.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Reid, and Arvind K

Reference 17

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Observation 50c134d6-496d-4352-a9e5-33a29d1e4289 · outbound

This paper cites RTSMS: Randomized Tucker with single-mode sketching.

Randomized algorithms for streaming low-rank approximation in tree tensor network format RTSMS: Randomized Tucker with single-mode sketching

Reference 18

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Randomized algorithms for streaming low-rank approximation in tree tensor network format Unresolved cited work

Reference 19

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Observation 9946f687-97a8-4824-bd93-7aef2823c358 · outbound

This paper cites High-dimensional probability.

Randomized algorithms for streaming low-rank approximation in tree tensor network format High-dimensional probability

Reference 20

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Randomized algorithms for streaming low-rank approximation in tree tensor network format Unresolved cited work

Reference 21

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Observation 8c895bb7-87e3-4e7c-8127-dc601e6908e3 · outbound

This paper cites New and improved Johnson –Lindenstrauss embeddings via the restricted isometry property.

Randomized algorithms for streaming low-rank approximation in tree tensor network format New and improved Johnson –Lindenstrauss embeddings via the restricted isometry property

Reference 22

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Source-reported events for the cited work

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Observation 162eb7b6-c57e-4ef7-b514-893c6fb369d9 · outbound

This paper cites Near-optimal hierarchical matrix approximation from matrix-vector products.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Near-optimal hierarchical matrix approximation from matrix-vector products

Reference 23

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Observation 0ee70a2b-5bc4-460e-9b4f-7b1f8789ad16 · outbound

This paper cites Fast and stable randomized low-rank matrix approximation.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Fast and stable randomized low-rank matrix approximation

Reference 24

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This paper cites Clarkson and David P.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Clarkson and David P

Reference 25

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Observation 19a28565-ddb2-43cc-b21a-12d03ec43a92 · outbound

This paper cites Tropp, Alp Yurtsever, Madeleine Udell, and Volk an Cevher.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Tropp, Alp Yurtsever, Madeleine Udell, and Volk an Cevher

Reference 26

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Observation 503c2700-6aaa-4c8e-885b-bb9c56d36c9c · outbound

This paper cites Low-rank Tucker approximation of a tensor from streaming data.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Low-rank Tucker approximation of a tensor from streaming data

Reference 27

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Observation fa351795-c851-411f-b5a4-9f17c586fda3 · outbound

This paper cites A multilinear Nystr¨ om algorithm for low-rank approxi- mation of tensors in Tucker format.

Randomized algorithms for streaming low-rank approximation in tree tensor network format A multilinear Nystr¨ om algorithm for low-rank approxi- mation of tensors in Tucker format

Reference 28

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Observation 3b381d8b-a0ab-4ce7-b455-852476513737 · outbound

This paper cites A sequential multili near Nystr¨ om algorithm for stream- ing low-rank approximation of tensors in Tucker format.

Randomized algorithms for streaming low-rank approximation in tree tensor network format A sequential multili near Nystr¨ om algorithm for stream- ing low-rank approximation of tensors in Tucker format

Reference 29

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Observation 03e09513-7cd8-4561-81e6-fb1d7f4f45cf · outbound

This paper cites Streaming tensor train approximation.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Streaming tensor train approximation

Reference 30

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Observation 9ec1a946-4482-45b7-91e5-0e06af5ef85e · outbound

This paper cites Clarkson and David P.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Clarkson and David P

Reference 31

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Observation de83f3a9-24d9-489d-bca1-c2f89b842234 · outbound

This paper cites Improved matrix a lgorithms via the subsampled random- ized Hadamard transform.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Improved matrix a lgorithms via the subsampled random- ized Hadamard transform

Reference 32

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Observation e6b49e88-7f9e-4e2a-9044-b6db1dff7580 · outbound

This paper cites A fast randomized alg orithm for overdetermined linear least-squares regression.

Randomized algorithms for streaming low-rank approximation in tree tensor network format A fast randomized alg orithm for overdetermined linear least-squares regression

Reference 33

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Observation 35423d3f-ec49-4af5-a344-80a2faf3a1b1 · outbound

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Randomized algorithms for streaming low-rank approximation in tree tensor network format Unresolved cited work

Reference 34

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Observation a121668c-703a-47f2-ba84-263f5adf9284 · outbound

This paper cites Tracking tensor ring decompositi ons of streaming tensors, 2023.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Tracking tensor ring decompositi ons of streaming tensors, 2023

Reference 35

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Observation fc0560b6-b4a6-4b4c-a81a-b145a0b02b37 · outbound

This paper cites On the optimal linear contrac- tion order of tree tensor networks, and beyond.

Randomized algorithms for streaming low-rank approximation in tree tensor network format On the optimal linear contrac- tion order of tree tensor networks, and beyond

Reference 36

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Observation 82fd89c4-b8ad-46bf-a18f-008ced6910b2 · outbound

This paper cites Tensor Spaces and Numerical Tensor Calculus , volume 56 of Springer Series in Computational Mathematics.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Tensor Spaces and Numerical Tensor Calculus , volume 56 of Springer Series in Computational Mathematics

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:13:04.033456Z

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Observation e9aa09c2-6076-418d-b786-bd4dcdbb9f67 · outbound

This paper cites Cost-eﬃcient Gaussian tensor network embeddings for tensor-structured inputs.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Cost-eﬃcient Gaussian tensor network embeddings for tensor-structured inputs

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:13:04.015525Z

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Observation 29662ad4-0043-412b-a014-4c0399624483 · outbound

This paper cites Ahle, Michael Kapralov, Jakob B.T.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Ahle, Michael Kapralov, Jakob B.T

Reference 39

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Observation b0807300-4865-4d9a-bb87-a04ecc55fa35 · outbound

This paper cites Near-Linear Time and Fixed-Parameter Tractable Algorithms for Tensor Decompositions.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Near-Linear Time and Fixed-Parameter Tractable Algorithms for Tensor Decompositions

Reference 40

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Observation f21ee44d-34fa-4219-bb2b-1217acee8021 · outbound

This paper cites A randomized tensor train singular value decomposition.

Randomized algorithms for streaming low-rank approximation in tree tensor network format A randomized tensor train singular value decomposition

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:13:03.979917Z

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Observation dbc12adb-96c2-4836-b229-13842f6678fd · outbound

This paper cites Randomized sketched TT-GMRES for linear systems with tensor structure.

Randomized algorithms for streaming low-rank approximation in tree tensor network format Randomized sketched TT-GMRES for linear systems with tensor structure

Reference 42

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Source-reported events for the cited work

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Observation ceaf1a05-d965-4f32-94fb-81537fd9f105 · outbound

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Randomized algorithms for streaming low-rank approximation in tree tensor network format TT-GMRES: solution to a linear system in the structured tensor format

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:13:03.962249Z

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