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Paper Citation Record · LEDGER

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems

As of 21 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2501.14107.

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

pith.paper-citation-record.v1
2501.14107 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:27:20.007743Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

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

22 of 22 outbound references displayed

  • verified exact2
  • verified fuzzy12
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1938c40f-f5d0-410e-9253-fb2905a2c129 · outbound

This paper cites an unresolved cited work.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Unresolved cited work

Reference 1

Resolution
verified exact
doi, observed 2026-08-10T15:27:20.053170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 26d457f6-62e3-44c7-92e7-397a5f10ea15 · outbound

This paper cites an unresolved cited work.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:27:20.315595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.938226Z digest=sha256:9b31e90a53a4e8c3003a168129653f513a25cb5c52aa2e5907e83ea82262fc7d

Observation 9a2219cc-238a-4755-b02e-2a514f66e5bd · outbound

This paper cites Accelerating bayesian inference over nonlinear differential equations with gaussian processes.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Accelerating bayesian inference over nonlinear differential equations with gaussian processes

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.305470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.941911Z digest=sha256:79ce33933c0b0715d5f8e2d54336da43905bee781bb03f5366e2c5cf51c6a3de

Observation 435aa64a-4fbf-4147-b7f4-45a9376264ec · outbound

This paper cites Ode parameter inference using adaptive gradient matching with gaussian processes.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Ode parameter inference using adaptive gradient matching with gaussian processes

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.295636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.945709Z digest=sha256:1df9b7d68bee4cbb4611272734abcc6b6e792712d65cbbf3c6604efbb950745b

Observation 9798744f-2da1-43bd-9491-e957cbb55f45 · outbound

This paper cites FitzHugh.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems FitzHugh

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.285951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.949212Z digest=sha256:faf3a56f51b4a669b64014ba8de37e97d44c76b5202cdcbea22581ebcaad2237

Observation 2b81557c-77b1-435b-a8a1-2cf8acd92745 · outbound

This paper cites Osborne, and Mark Girolami.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Osborne, and Mark Girolami

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.275137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.956777Z digest=sha256:87793ead0f2a6b1f600510d8a6fed5e2c10d9b2ab21e08b83bed0bc5e201377a

Observation 84e0a346-99e5-445a-b097-56a1ce14e7c1 · outbound

This paper cites Hirata, S.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Hirata, S

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.266257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.959825Z digest=sha256:e3b1afb2764cd4d71fe5912769669d28fa25dde5cb032eea1ad73b2fb705131b

Observation 8ef35189-67b1-4885-9f27-fd70def6def3 · outbound

This paper cites Bayesian calibration of computer models.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Bayesian calibration of computer models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:19.963384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:19.963384Z digest=sha256:b0942755719d783263e0d7d920354724deb809709cf480a7c9aac05c3044f917

Observation 39f6145b-01b2-41fc-a6f3-51c7a6b1bc39 · outbound

This paper cites Lapidus and J.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Lapidus and J

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.251795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.966451Z digest=sha256:d7100dde0724077e40013546a6a42dbe7494d60b50cacb08484e38d5e4f09baa

Observation 5c1d7cb4-8a3b-4a0f-bdf8-603ceb044ade · outbound

This paper cites Parameter inference based on gaussian processes informed by nonlinear partial differential equations.SIAM/ASA Journal on Uncertainty Quan- tification, 12(3):964–1004, 2024.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Parameter inference based on gaussian processes informed by nonlinear partial differential equations.SIAM/ASA Journal on Uncertainty Quan- tification, 12(3):964–1004, 2024

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.243390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.970137Z digest=sha256:5882f0c0d6eb5251913e28cc012369cc146ab092dc5b38e90e51127e2e512535

Observation be290ea0-89ef-4dac-857f-6724322bdfa6 · outbound

This paper cites Fourier neural operator for parametric partial differential equations.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Fourier neural operator for parametric partial differential equations

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.233169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation e1a95728-de1c-41d7-a9e8-6175b09687a7 · outbound

This paper cites an unresolved cited work.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Unresolved cited work

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:19.976549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:19.976549Z digest=sha256:a494e3385bd571b21e4556f94f1994f1a29a32eabe4044f74dfee0f550a9274f

Observation 7d1525bb-ee9f-4bc1-bce8-3dedc990006b · outbound

This paper cites Nagumo, S.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Nagumo, S

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:19.979585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:19.979585Z digest=sha256:7fbffc830c252d17457e2a3e40e66e18808b4524bb5d69eeae0ba16fec65147d

Observation d83bf80e-4ce1-4662-99df-a7676a18300a · outbound

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

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:19.982761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:19.982761Z digest=sha256:309c168422f33089447579758b10501b17e764b25260e1000c932f5204dd7fc1

Observation abdd9c05-7120-4fbc-8645-e0e9c0f57741 · outbound

This paper cites Parameter estimation for differential equations: a generalized smoothing approach.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Parameter estimation for differential equations: a generalized smoothing approach

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.212424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.985983Z digest=sha256:d75621dd2f56728ce1852837b636570014fb1143f2419854d8e259043eb10ebb

Observation 83d0e462-c48d-432a-bb0f-7139a55a7486 · outbound

This paper cites an unresolved cited work.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:27:20.202258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.989100Z digest=sha256:a1a6bb7150c7a9fbcc280ff14323bbba4e6fc5faff375bf27cb0aea738b8a2bc

Observation 503c92bf-aeb7-42be-80a1-771e9d72673e · outbound

This paper cites Zero-shot Imputation with Foundation Inference Models for Dynamical Systems.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Zero-shot Imputation with Foundation Inference Models for Dynamical Systems

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:19.992117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:19.992117Z digest=sha256:0bc217643f3fe2bd52206d6124492fb2250c6d72ecfd928415ec8d3f75416d18

Observation f3fb8e91-b843-489f-ac68-4fa168bada0a · outbound

This paper cites Understanding and mitigating gradient flow pathologies in physics-informed neural networks.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Understanding and mitigating gradient flow pathologies in physics-informed neural networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:19.996438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:19.996438Z digest=sha256:abac2d354cfe79f86777ca5a2412ad8b36e82c0030de2c3917ea7ba90f175052

Observation 9331e2c0-d61d-44af-8b16-4b3e5e81672a · outbound

This paper cites Gaussian processes for bayesian estimation in ordinary differential equations.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Gaussian processes for bayesian estimation in ordinary differential equations

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.192249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:19.999588Z digest=sha256:4551258a553db57ce8a48c547e585ad47b3e8c43d2dba7bab6ca8a4805a75ff4

Observation 074513ae-0c67-4dfe-99cc-ead80abdf89c · outbound

This paper cites Gorbach, Andreas Krause, and Joachim M.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Gorbach, Andreas Krause, and Joachim M

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.181744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:20.002472Z digest=sha256:74aa223dbf416dbcf9b079bd77b77ced1c37aa5312a2e84ff2953f5006b5253e

Observation bebf6d5e-7e99-4316-a219-f37b6caa0c66 · outbound

This paper cites Osborne, Bernhard Sch¨ olkopf, Andreas Krause, and Stefan Bauer.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Osborne, Bernhard Sch¨ olkopf, Andreas Krause, and Stefan Bauer

Reference 22

Resolution
verified exact
doi, observed 2026-08-10T15:27:20.035524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:20.005172Z digest=sha256:ee0a2902bac8963eadbcc921f2554b57e8db0a271fa7b0f833bb112550987bd7

Observation bbfae840-b2a0-422e-8f32-2bcf35ee6246 · outbound

This paper cites Inference of dynamic systems from noisy and sparse data via manifold-constrained gaussian processes.

EFiGP: Eigen-Fourier Physics-Informed Gaussian Process for Inference of Dynamic Systems Inference of dynamic systems from noisy and sparse data via manifold-constrained gaussian processes

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:27:20.172372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:27:20.007743Z digest=sha256:75705f37b12c1a692a132d3321ef2ca04c28bd4ed573ec3919daf15f7913a4ec

Pith citing papers

No inbound Pith citation observations are available.