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Paper Citation Record · LEDGER

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2506.07604.

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

pith.paper-citation-record.v1
2506.07604 v1

Coverage vector

measured 42 of 42 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T20:43:48.885047Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-18T20:46:51.711756Z

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation 721ff72f-0186-416b-b437-aac3f78339b6 · outbound

This paper cites A new look at the statistical model identification.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data A new look at the statistical model identification

Reference 1

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Observation a811e787-dd64-446d-9d0b-2aa434c27d34 · outbound

This paper cites Fitting ordinary differential equations to chaotic data.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Fitting ordinary differential equations to chaotic data

Reference 2

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This paper cites A new method for the identification of systems.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data A new method for the identification of systems

Reference 3

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Observation f8d964e0-af28-4120-90be-a71609aa5c88 · outbound

This paper cites Least squares methods.Handbook of numerical analysis , 1:465–652, 1990.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Least squares methods.Handbook of numerical analysis , 1:465–652, 1990

Reference 4

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Observation ded340a5-ca75-4fa3-a485-8ddc42f45ab4 · outbound

This paper cites Error analysis of least squares algorithms.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Error analysis of least squares algorithms

Reference 5

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This paper cites Automated reverse engineering of nonlinear dynamical systems.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Automated reverse engineering of nonlinear dynamical systems

Reference 6

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Observation 150907bc-30a7-4938-8260-cadcc6758a67 · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynamical systems.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Reference 7

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Observation bced41ae-ef17-4de0-89ba-2abb50420a59 · outbound

This paper cites Subspace pursuit for compressive sensing signal reconstruction.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Subspace pursuit for compressive sensing signal reconstruction

Reference 8

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This paper cites Uncertainty principles and ideal atomic decomposition.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Uncertainty principles and ideal atomic decomposition

Reference 9

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Observation 9e16bc5c-97bd-4514-9628-8b809c509796 · outbound

This paper cites Coherence pattern–guided compressive sensing with un- resolved grids.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Coherence pattern–guided compressive sensing with un- resolved grids

Reference 10

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Observation 701f3a60-9cb0-4970-aecb-6c18a370a5b5 · outbound

This paper cites On sparse representations in arbitrary redundant bases.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data On sparse representations in arbitrary redundant bases

Reference 11

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Observation 88b373fc-1723-4cb0-90d9-372930f1c12a · outbound

This paper cites Robust and optimal sparse regression for nonlinear pde models.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Robust and optimal sparse regression for nonlinear pde models

Reference 12

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This paper cites Uniformly high order accurate essentially non-oscillatory schemes, iii.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Uniformly high order accurate essentially non-oscillatory schemes, iii

Reference 13

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This paper cites Group projected subspace pursuit for block sparse signal reconstruction: Convergence analysis and applications.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Group projected subspace pursuit for block sparse signal reconstruction: Convergence analysis and applications

Reference 14

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Observation 787aab88-3365-402b-ab79-c10e7d83e107 · outbound

This paper cites Robust identification of differential equations by numerical techniques from a single set of noisy observation.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Robust identification of differential equations by numerical techniques from a single set of noisy observation

Reference 15

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This paper cites Group projected subspace pursuit for identification of variable coefficient differential equations (gp-ident).

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Group projected subspace pursuit for identification of variable coefficient differential equations (gp-ident)

Reference 16

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Observation 996863e9-9c71-499c-bbb9-a8e1dc7217e8 · outbound

This paper cites Asymptotic the- ory of-regularized pde identification from a single noisy trajectory.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Asymptotic the- ory of-regularized pde identification from a single noisy trajectory

Reference 17

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Observation bb3b42fe-aaf4-4273-b63d-c1b08dfdb6d2 · outbound

This paper cites How much can one learn a partial differential equation from its solution? Foundations of Computational Mathematics , 24(5):1595–1641, 2024.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data How much can one learn a partial differential equation from its solution? Foundations of Computational Mathematics , 24(5):1595–1641, 2024

Reference 18

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Observation 5ca31d74-e6fa-4467-835b-244ae531720c · outbound

This paper cites The distribution of the flora in the alpine zone.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data The distribution of the flora in the alpine zone

Reference 19

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Observation 85e52fe8-e90a-4e11-99c2-698cbc63d5d7 · outbound

This paper cites Block subspace pursuit for block-sparse signal reconstruction.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Block subspace pursuit for block-sparse signal reconstruction

Reference 20

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This paper cites Ident: Identifying differential equations with numerical time evolution.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Ident: Identifying differential equations with numerical time evolution

Reference 21

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This paper cites Benchmarking sparse system identification with low-dimensional chaos.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Benchmarking sparse system identification with low-dimensional chaos

Reference 22

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data ¨Uber die beste ann¨ aherung von funktionen einer gegebenen funktionen- klasse

Reference 23

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This paper cites Surfaces generated by moving least squares methods.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Surfaces generated by moving least squares methods

Reference 24

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This paper cites Robust low-rank discovery of data- driven partial differential equations.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Robust low-rank discovery of data- driven partial differential equations

Reference 25

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Weak sindy for partial differential equations

Reference 26

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Weak sindy: Galerkin-based data-driven model selection

Reference 27

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Parameter identification techniques for partial differential equations

Reference 28

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Using noisy or incomplete data to discover models of spatiotemporal dynamics

Reference 29

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Data-driven iden- tification of parametric partial differential equations

Reference 30

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Rudy, Alessandro Alla, Steven L

Reference 31

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This paper cites Data-driven discovery of partial differential equations.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Data-driven discovery of partial differential equations

Reference 32

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This paper cites Learning partial differential equations via data discovery and sparse opti- mization.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Learning partial differential equations via data discovery and sparse opti- mization

Reference 33

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Observation 4d7c9041-09e8-40f8-9b10-110af6391d94 · outbound

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Distilling free-form natural laws from experimental data

Reference 34

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Source-reported events for the cited work

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This paper cites Cross-validation: A review.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Cross-validation: A review

Reference 35

Resolution
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This paper cites He, and Hao Liu.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data He, and Hao Liu

Reference 36

Resolution
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Observation ec2c6460-cd65-4c59-819d-caf5fece6192 · outbound

This paper cites Weakident: Weak formulation for identifying differential equation using narrow-fit and trimming.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Weakident: Weak formulation for identifying differential equation using narrow-fit and trimming

Reference 37

Resolution
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Observation bb24d82e-f62c-4b51-aad2-18208d1cf87c · outbound

This paper cites Fourier Features for Identifying Differential Equations (FourierIdent).

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Fourier Features for Identifying Differential Equations (FourierIdent)

Reference 38

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Regression shrinkage and selection via the lasso

Reference 39

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Just relax: Convex programming methods for subset selection and sparse approximation

Reference 40

Resolution
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This paper cites Just relax: Convex programming methods for identifying sparse signals in noise.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Just relax: Convex programming methods for identifying sparse signals in noise

Reference 41

Resolution
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Observation 68990a9e-8354-40f2-850d-215b719904f0 · outbound

This paper cites Model selection and estimation in regression with grouped variables.

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data Model selection and estimation in regression with grouped variables

Reference 42

Resolution
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Pith citing papers

Observation 4b5c5b99-b6e2-4c21-8cfb-539c36343936 · inbound

Stoch-IDENT: New Method and Mathematical Analysis for Identifying SPDEs from Data cites this paper.

Stoch-IDENT: New Method and Mathematical Analysis for Identifying SPDEs from Data IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data

Reference 31

Resolution
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