Paper Citation Record · LEDGER

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling

As of 13 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.27728.

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pith.paper-citation-record.v1
2607.27728 v1

Coverage vector

measured 37 of 37 reference resolution

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Reference resolution

37 of 37 outbound references displayed

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Outbound references

Observation 00b157a7-38a9-483d-941e-f04393818b9e · outbound

This paper cites Communication in the Presence of Noise,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Communication in the Presence of Noise,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:44.423002Z

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Observation 4cae4d99-fdb0-4b7a-bf00-e9a6c6e4f849 · outbound

This paper cites Sampling-50 years after Shannon,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Sampling-50 years after Shannon,

Reference 2

Resolution: verified exact; doi, observed 2026-08-01T02:41:26.039003Z

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Observation 05c92e7c-dcd6-4a30-b255-e9a3840ba2ea · outbound

This paper cites an unresolved cited work.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Unresolved cited work

Reference 3

Resolution: verified exact; doi, observed 2026-08-01T02:41:25.809802Z

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Observation 29e1c9af-7540-4c8a-a8ba-f2b895f91f2b · outbound

This paper cites A generalized Nyquist-Shannon sampling theorem using the Koopman operator,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling A generalized Nyquist-Shannon sampling theorem using the Koopman operator,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:44.749257Z

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Observation 98cad6ca-06f0-4453-8b67-1e6579823924 · outbound

This paper cites Capture method for digital twin of formation processes of sand bars,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Capture method for digital twin of formation processes of sand bars,

Reference 5

Resolution: verified exact; doi, observed 2026-08-01T02:41:25.658916Z

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Observation 37582d24-3738-4516-ac83-e56bba2604e3 · outbound

This paper cites On the occurrence of sandbars,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling On the occurrence of sandbars,

Reference 6

Resolution: verified exact; doi, observed 2026-08-01T02:41:25.478247Z

Source-reported events for the cited work

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Observation e2dbc862-e945-4454-af66-5682e4afb35c · outbound

This paper cites Physics-informed neural networks for inversion of river flow and geometry with shallow water model,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Physics-informed neural networks for inversion of river flow and geometry with shallow water model,

Reference 7

Resolution: verified exact; doi, observed 2026-08-01T02:41:25.217185Z

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Observation 628d32da-e9d2-4200-8916-6290006d358b · outbound

This paper cites Acceleration-induced laminarization of sheet flow over smooth steep slopes,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Acceleration-induced laminarization of sheet flow over smooth steep slopes,

Reference 8

Resolution: verified exact; doi, observed 2026-08-01T02:41:25.048322Z

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Observation 8684bbf7-08d6-4b74-8d70-8d22c83257a4 · outbound

This paper cites an unresolved cited work.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Unresolved cited work

Reference 9

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Observation ef7b1662-99ae-4e34-8828-aac094b835eb · outbound

This paper cites an unresolved cited work.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:45.187228Z

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Observation 7b003d54-0a83-438b-91a7-edf0975c0a2e · outbound

This paper cites Strang,Linear Algebra and Learning from Data.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Strang,Linear Algebra and Learning from Data

Reference 11

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.892839Z

Source-reported events for the cited work

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Observation c13d8b52-eedc-49d7-9691-5864b67b7b56 · outbound

This paper cites Physics-informed dynamic mode decomposition,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Physics-informed dynamic mode decomposition,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:45.423565Z

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Observation 118e69c6-57f4-48f2-8e60-f7ded9ed9099 · outbound

This paper cites Multi-Resolution Convolutional Dictionary Learning for Riverbed Dynamics Modeling,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Multi-Resolution Convolutional Dictionary Learning for Riverbed Dynamics Modeling,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:45.520978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e31e5216-ac4d-4622-8554-e0b94dea8d08 · outbound

This paper cites Mauroy, I.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Mauroy, I

Reference 14

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Unavailable: canonical work link unavailable.

Observation 8912425e-6788-4901-85ad-52dbc638cd88 · outbound

This paper cites A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:45.724888Z

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Observation cb3cd13a-fd54-48ff-b146-98ffda6f0c4b · outbound

This paper cites Data-driven spectral analysis of the Koopman operator,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Data-driven spectral analysis of the Koopman operator,

Reference 16

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.728256Z

Source-reported events for the cited work

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Observation 8277896a-107f-4f48-9db3-d4653b719502 · outbound

This paper cites Self-supervised Koopman operator learning for distributed final synchronization prediction of networked nonlinear dynamics,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Self-supervised Koopman operator learning for distributed final synchronization prediction of networked nonlinear dynamics,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:46.083467Z

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Observation 1accba4b-1afc-43c8-9f4c-427d2b8abb16 · outbound

This paper cites Discovering Mathematical Expressions Through DeepSymNet: A Classification- Based Symbolic Regression Framework,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Discovering Mathematical Expressions Through DeepSymNet: A Classification- Based Symbolic Regression Framework,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:46.312919Z

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Observation 9b49aea4-531b-4596-bb30-4daccbb8baec · outbound

This paper cites Data-driven discovery of governing differential equations across physical systems.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Data-driven discovery of governing differential equations across physical systems

Reference 19

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Observation 5e4f3ea2-d338-4616-ac18-16706e850846 · outbound

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

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Data-driven discovery of partial differential equations,

Reference 20

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Observation 96142f04-1225-4f54-9aa9-4802850973c9 · outbound

This paper cites Symbolic genetic algorithm for discovering open-form partial differential equations (SGA- PDE),.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Symbolic genetic algorithm for discovering open-form partial differential equations (SGA- PDE),

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:46.551017Z

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Observation 6fbec7bc-1772-41db-95db-ecfc8d81e552 · outbound

This paper cites DISCOVER: Deep identification of symbolically concise open-form partial differential equations via enhanced reinforcement learning,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling DISCOVER: Deep identification of symbolically concise open-form partial differential equations via enhanced reinforcement learning,

Reference 22

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.626504Z

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Observation ace1f0ce-d4e1-4566-9773-af977431b241 · outbound

This paper cites How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:46.697727Z

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Observation a2796101-2ed1-4182-b7f7-c60e3b0f81e3 · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:46.871089Z

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Observation 2dc1102d-74c6-404e-926e-b0f37a0091de · outbound

This paper cites Partial Differential Equations Meet Deep Neural Networks: A Survey,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Partial Differential Equations Meet Deep Neural Networks: A Survey,

Reference 25

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Observation 72f75a1f-97f5-41f2-9ef8-95cbb6404f99 · outbound

This paper cites Koopman Spectral Linearization vs. Carleman Linearization: A Computational Comparison Study,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Koopman Spectral Linearization vs. Carleman Linearization: A Computational Comparison Study,

Reference 26

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.483823Z

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This paper cites Discrete Cosine Transform,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Discrete Cosine Transform,

Reference 27

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Observation dc727081-4b71-4bd5-827b-edc1d912cb68 · outbound

This paper cites Ochoa-Dominguez and K.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Ochoa-Dominguez and K

Reference 28

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Observation b5fc9f07-5057-47e5-9e01-d4f3a253b250 · outbound

This paper cites Algorithms for the integration and derivation of Chebyshev series,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Algorithms for the integration and derivation of Chebyshev series,

Reference 29

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Observation 2ebc941c-4974-4114-9146-d28c2efde97c · outbound

This paper cites Numerical Spectrum Linking: Identi- fication of Governing PDE via Koopman-Chebyshev Approximation,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Numerical Spectrum Linking: Identi- fication of Governing PDE via Koopman-Chebyshev Approximation,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:47.757254Z

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Observation 8b032847-a464-4283-ab34-dcd40aa31fcc · outbound

This paper cites An overview of Koopman-based control: From error bounds to closed-loop guarantees,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling An overview of Koopman-based control: From error bounds to closed-loop guarantees,

Reference 31

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Observation 269b793d-1a48-45af-9a72-fdbc69a9d6eb · outbound

This paper cites Reduced Order Data-Driven Twin Models for Nonlinear PDEs by Randomized Koopman Orthogonal Decomposition and Explainable Deep Learning,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Reduced Order Data-Driven Twin Models for Nonlinear PDEs by Randomized Koopman Orthogonal Decomposition and Explainable Deep Learning,

Reference 32

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.373802Z

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Observation f1439351-195c-486b-b09f-3d134747e920 · outbound

This paper cites Chebyshev Polynomials,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Chebyshev Polynomials,

Reference 33

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Observation 49e3c6d9-e6ce-4016-bbc6-bfb124f99d24 · outbound

This paper cites Shifted Chebyshev polynomials based solution of partial differential equations,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Shifted Chebyshev polynomials based solution of partial differential equations,

Reference 34

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.257758Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0162b4d7-0b6e-4d48-b477-a951d27e8571 · outbound

This paper cites Representing derivatives of Chebyshev polynomials by Chebyshev polynomials and related questions,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Representing derivatives of Chebyshev polynomials by Chebyshev polynomials and related questions,

Reference 35

Resolution: verified exact; doi, observed 2026-08-01T02:41:24.145130Z

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Observation 89723d86-70b7-404a-b83d-99a9f90acf47 · outbound

This paper cites Derivations and Identities for Chebyshev Polynomials,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Derivations and Identities for Chebyshev Polynomials,

Reference 36

Resolution: verified exact; doi, observed 2026-08-01T02:41:23.975091Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f99a002d-dd8b-4a21-86d4-3f8da2f96537 · outbound

This paper cites Data-Driven Koopman Based System Identification for Partially Observed Dynamical Systems with Input and Disturbance,.

Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation with Resampling Data-Driven Koopman Based System Identification for Partially Observed Dynamical Systems with Input and Disturbance,

Reference 37

Resolution: verified exact; doi, observed 2026-08-01T02:41:23.785868Z

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