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Paper Citation Record · LEDGER

Sketch low-rank dynamics: orthogonal vs. oblique projections

As of 9 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.03402.

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

pith.paper-citation-record.v1
2607.03402 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T02:45:04.789174Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation a2abf236-6075-40a4-bf89-c592e061bfd7 · outbound

This paper cites Optimization algorithms on matrix manifolds.

Sketch low-rank dynamics: orthogonal vs. oblique projections Optimization algorithms on matrix manifolds

Reference 1

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Observation 8b7a7fab-d19d-45f7-8639-dc4ca88add82 · outbound

This paper cites Approximate nearest neighbors and the fast Johnson--Lindenstrauss transform.

Sketch low-rank dynamics: orthogonal vs. oblique projections Approximate nearest neighbors and the fast Johnson--Lindenstrauss transform

Reference 2

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Observation d4a03333-90b5-4779-8f97-73351d830c36 · outbound

This paper cites A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening.

Sketch low-rank dynamics: orthogonal vs. oblique projections A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening

Reference 3

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:c40d4cb358a812b5e2e30f108c6d9b429c8974c839900e067a9b1c0192186988

Observation fb239d8b-f223-4824-9a78-20f269e35fcc · outbound

This paper cites Randomized Cholesky QR factorizations.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized Cholesky QR factorizations

Reference 4

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:eb6f13d0803bd379912ab246063a96b08e9146235d932fb9411ba95b445914fe

Observation ba13a085-b908-4ec8-aa71-6b597afe828e · outbound

This paper cites Randomized Gram--Schmidt process with application to GMRES.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized Gram--Schmidt process with application to GMRES

Reference 5

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:1e792533a243ed97b06fd8c31d35f4a5186421af9aa13e29359e111d9ae7138a

Observation 329619a1-67a7-4ae2-9bdf-c74cec1dfe4d · outbound

This paper cites Randomized block Gram--Schmidt process for the solution of linear systems and eigenvalue problems.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized block Gram--Schmidt process for the solution of linear systems and eigenvalue problems

Reference 6

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:a3c967648b790f6c6c235e1852116837310c5d0ea970730bb219154725b76df9

Observation 3eaec8e4-5999-4e1b-877b-1bae03155774 · outbound

This paper cites Randomized linear algebra for model reduction.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized linear algebra for model reduction

Reference 7

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:2d70b23bca9e260cdd28681bbef990f074c8db073925825a0c2e557eb34f69b5

Observation 423b0b7f-b9e3-40a3-9414-5d9c123fdc87 · outbound

This paper cites Randomized linear algebra for model reduction.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized linear algebra for model reduction

Reference 8

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:1b3bb09331e1f928b8cbddcc05d32ec7f8c913095fcf0efbbf4dbceedc3d5813

Observation 49e6c95a-9dcd-4551-a108-3d9d21079865 · outbound

This paper cites Randomized methods for dynamical low-rank approximation.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized methods for dynamical low-rank approximation

Reference 9

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:fd4a97c2e1639f9e145ed292dc4af504fadaf08496e092e96ff9f8d4f03d5897

Observation 6cd63e84-f65e-47f5-8291-c69bf69fdcf4 · outbound

This paper cites Projected exponential methods for stiff dynamical low-rank approximation problems.

Sketch low-rank dynamics: orthogonal vs. oblique projections Projected exponential methods for stiff dynamical low-rank approximation problems

Reference 10

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:f59bc3fcae12e3033f8b48e0a8ba40f651bb1fa15735a1ddc5b735d48ae47e87

Observation aef08251-a535-45f8-83c4-c44eda630ee8 · outbound

This paper cites Low-rank Parareal : a low-rank parallel-in-time integrator.

Sketch low-rank dynamics: orthogonal vs. oblique projections Low-rank Parareal : a low-rank parallel-in-time integrator

Reference 11

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:5f6f4ecfc08d238f9bd387cde68674f17ff566a39d3fc735306fdc72f9d0774b

Observation 10d89486-f4e2-4863-b80f-a102fc208d89 · outbound

This paper cites Interpolatory dynamical low-rank approximation: Theoretical foundations and algorithms.

Sketch low-rank dynamics: orthogonal vs. oblique projections Interpolatory dynamical low-rank approximation: Theoretical foundations and algorithms

Reference 12

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:c6d35c90abef628422d5dd588e6e853f4307119ea20039d63121fe2aa196d22a

Observation e330beea-b8ba-4166-8c4d-8301b236f63b · outbound

This paper cites An unconventional robust integrator for dynamical low-rank approximation.

Sketch low-rank dynamics: orthogonal vs. oblique projections An unconventional robust integrator for dynamical low-rank approximation

Reference 13

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:fca793b7fb2e307667d33078438452a698df02914ca0be4339f28ff4b6d4a861

Observation 0a181956-de19-48cb-a5f3-22205026aece · outbound

This paper cites A rank-adaptive robust integrator for dynamical low-rank approximation.

Sketch low-rank dynamics: orthogonal vs. oblique projections A rank-adaptive robust integrator for dynamical low-rank approximation

Reference 14

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:a4a5a9c65564f27dc87a8e6b0fa94bf024218df4b18c7e555838358f602f0523

Observation a5ffd71c-53a5-4262-8fda-3ddbfe6c3c36 · outbound

This paper cites A robust second-order low-rank BUG integrator based on the midpoint rule.

Sketch low-rank dynamics: orthogonal vs. oblique projections A robust second-order low-rank BUG integrator based on the midpoint rule

Reference 15

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:88427f0d8a6cc61f69653fa05294b44ba5eeda4d7d3bd704406c7fd08fea9991

Observation 2dd5eb48-da72-4b9c-b766-ede1e03ba3f2 · outbound

This paper cites The integration of the Vlasov equation in configuration space.

Sketch low-rank dynamics: orthogonal vs. oblique projections The integration of the Vlasov equation in configuration space

Reference 16

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Observation 3d01b6ab-8560-4b0c-a402-071f989ae769 · outbound

This paper cites Randomized implicitly restarted Arnoldi method for the non-symmetric eigenvalue problem.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized implicitly restarted Arnoldi method for the non-symmetric eigenvalue problem

Reference 17

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Observation ca926414-4e24-4200-9fc9-4ab4665d159f · outbound

This paper cites Randomized orthogonalization and Krylov subspace methods: principles and algorithms.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized orthogonalization and Krylov subspace methods: principles and algorithms

Reference 18

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Observation 9be93c38-0111-42c6-8bae-e95d2b2b227f · outbound

This paper cites Rank-adaptive tensor methods for high-dimensional nonlinear PDEs.

Sketch low-rank dynamics: orthogonal vs. oblique projections Rank-adaptive tensor methods for high-dimensional nonlinear PDEs

Reference 19

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:80c08b6e36694bc7d68ffb55721d8088fd860c88e2cf3c45245ef6ee486eacd7

Observation 0936cb93-2e98-4cd7-8403-c8782b21daa6 · outbound

This paper cites Communication-optimal parallel and sequential QR and LU factorizations.

Sketch low-rank dynamics: orthogonal vs. oblique projections Communication-optimal parallel and sequential QR and LU factorizations

Reference 20

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Observation d866ac04-ff4a-4b76-b6ae-0c41b5e8f488 · outbound

This paper cites A low-rank algorithm for weakly compressible flow.

Sketch low-rank dynamics: orthogonal vs. oblique projections A low-rank algorithm for weakly compressible flow

Reference 21

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:3572857f92c81ee5a382f3715b185e92d539dc4461c53a9e1dcf923c56d487e5

Observation 59f86066-aed4-4e00-964a-73870646815a · outbound

This paper cites A mass, momentum, and energy conservative dynamical low-rank scheme for the Vlasov equation.

Sketch low-rank dynamics: orthogonal vs. oblique projections A mass, momentum, and energy conservative dynamical low-rank scheme for the Vlasov equation

Reference 22

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:38004de6880e3479cdd386471be9544554b994024422350bca58b838d21863fe

Observation a7d5b5f5-5d78-46d3-8b6c-7842d64d337e · outbound

This paper cites A low-rank projector-splitting integrator for the Vlasov--Poisson equation.

Sketch low-rank dynamics: orthogonal vs. oblique projections A low-rank projector-splitting integrator for the Vlasov--Poisson equation

Reference 23

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Observation 19879464-e49f-4d9c-b7a6-312dc1a6d286 · outbound

This paper cites A quasi-conservative dynamical low-rank algorithm for the Vlasov equation.

Sketch low-rank dynamics: orthogonal vs. oblique projections A quasi-conservative dynamical low-rank algorithm for the Vlasov equation

Reference 24

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Observation f5e993ea-aef9-4c54-b2f3-944217c09a4f · outbound

This paper cites Comparison of Eulerian Vlasov solvers.

Sketch low-rank dynamics: orthogonal vs. oblique projections Comparison of Eulerian Vlasov solvers

Reference 25

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Observation 06d6f896-dacc-4afe-bdac-22729c448357 · outbound

This paper cites Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions.

Sketch low-rank dynamics: orthogonal vs. oblique projections Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions

Reference 26

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Observation eb8b4622-3ef8-4396-9a4d-5ef67defece4 · outbound

This paper cites Analysis of randomized Householder--Cholesky QR factorization with multisketching.

Sketch low-rank dynamics: orthogonal vs. oblique projections Analysis of randomized Householder--Cholesky QR factorization with multisketching

Reference 27

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Observation 546509d7-345c-45b3-8fed-d5e1972b194d · outbound

This paper cites Projection methods for dynamical low-rank approximation of high-dimensional problems.

Sketch low-rank dynamics: orthogonal vs. oblique projections Projection methods for dynamical low-rank approximation of high-dimensional problems

Reference 28

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Observation fdfee4ed-963b-4d08-a100-368d69deb2a6 · outbound

This paper cites Discretized dynamical low-rank approximation in the presence of small singular values.

Sketch low-rank dynamics: orthogonal vs. oblique projections Discretized dynamical low-rank approximation in the presence of small singular values

Reference 29

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Observation 867aa35f-8d6d-4192-bb4f-86aadef0a6c6 · outbound

This paper cites Dynamical low-rank approximation.

Sketch low-rank dynamics: orthogonal vs. oblique projections Dynamical low-rank approximation

Reference 30

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:cdba6c83b1856374e32005a82499a4990cc618d6d028cc3eaa09e824ce3b0a78

Observation c453d25a-6de5-47e8-90d6-b702963b620b · outbound

This paper cites Randomized low-rank Runge--Kutta methods.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized low-rank Runge--Kutta methods

Reference 31

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Observation 81ea197b-d8ec-4513-8b29-b83832d584d3 · outbound

This paper cites A projector-splitting integrator for dynamical low-rank approximation.

Sketch low-rank dynamics: orthogonal vs. oblique projections A projector-splitting integrator for dynamical low-rank approximation

Reference 32

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Observation e8581a4a-d3f3-42a9-abaa-c9e23225ea3c · outbound

This paper cites Randomized numerical linear algebra: Foundations and algorithms.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized numerical linear algebra: Foundations and algorithms

Reference 33

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Observation d3f206ca-8556-4db8-93e9-4fea345befe9 · outbound

This paper cites Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software.

Sketch low-rank dynamics: orthogonal vs. oblique projections Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software

Reference 34

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Observation 95e63dc7-a91b-4714-ba30-74c8396f318e · outbound

This paper cites Error analysis of the dynamically orthogonal approximation of time dependent random PDEs.

Sketch low-rank dynamics: orthogonal vs. oblique projections Error analysis of the dynamically orthogonal approximation of time dependent random PDEs

Reference 35

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Observation 96f0acf9-921f-4285-88d8-261d5586a30b · outbound

This paper cites Fast and accurate randomized algorithms for linear systems and eigenvalue problems.

Sketch low-rank dynamics: orthogonal vs. oblique projections Fast and accurate randomized algorithms for linear systems and eigenvalue problems

Reference 36

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:08f8ebfd94fb44904a8945e5f19b6bf317c860be21e37916d4e8dc11dfcfb81e

Observation b0e3ba85-82f2-4459-b79a-cc21780ded87 · outbound

This paper cites Dynamically orthogonal field equations for continuous stochastic dynamical systems.

Sketch low-rank dynamics: orthogonal vs. oblique projections Dynamically orthogonal field equations for continuous stochastic dynamical systems

Reference 37

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:ae80214e832d458b448b0245026d988f04fb9b8dc7eadae04f1ae7ae1f4ee721

Observation 36f94063-271f-43f5-b87b-8ca855053f8b · outbound

This paper cites Improved approximation algorithms for large matrices via random projections.

Sketch low-rank dynamics: orthogonal vs. oblique projections Improved approximation algorithms for large matrices via random projections

Reference 38

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:d30ad8799a992ea1c4f6bdd85759e146fcd56fd04a15cf0d5f0a64186f3796fe

Observation 91c6ee74-78eb-4a21-a937-306ecbe939a5 · outbound

This paper cites Practical sketching algorithms for low-rank matrix approximation.

Sketch low-rank dynamics: orthogonal vs. oblique projections Practical sketching algorithms for low-rank matrix approximation

Reference 39

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:3dcaf13e564216c482f6c8bf6a950501ba95597c280e5b0d1cbe04e4d92809f2

Observation a6d13c5e-f894-43be-b3f6-56d4cbcd0e1c · outbound

This paper cites Low-rank matrix completion by Riemannian optimization.

Sketch low-rank dynamics: orthogonal vs. oblique projections Low-rank matrix completion by Riemannian optimization

Reference 40

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:52ed794a7de324055f881cd740f8a333da746c8a9f94fc76d9f1cb7e2804c5e6

Observation 61b77449-7f8c-4251-afed-31bd8102b191 · outbound

This paper cites Sketching as a tool for numerical linear algebra.

Sketch low-rank dynamics: orthogonal vs. oblique projections Sketching as a tool for numerical linear algebra

Reference 41

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source=arxiv_source observed=2026-07-12T02:45:04.789174Z digest=sha256:3454024051ab9c5f53934629fd0ed3339efbf7d0967237d44d38f6413dc36f29

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