Paper Citation Record · LEDGER

AI Feynman: a Physics-Inspired Method for Symbolic Regression

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:1905.11481.

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

pith.paper-citation-record.v1
1905.11481 v2

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measured 18 of 18 standing notices

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

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:28:25.041953Z

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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Outbound references

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Pith citing papers

Observation 65ac8bd1-b6e2-45df-9991-5099fcf0c8a5 · inbound

Statistical Patterns in the Equations of Physics and the Emergence of a Meta-Law of Nature cites this paper.

Statistical Patterns in the Equations of Physics and the Emergence of a Meta-Law of Nature AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:53:29.650804Z

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Observation 95774d0f-2fee-4736-8396-ac1456d9d8b5 · inbound

On the definition and importance of interpretability in scientific machine learning cites this paper.

On the definition and importance of interpretability in scientific machine learning AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 74

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T14:11:38.696797Z

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Observation f9ed15a5-da87-45f5-b13a-4b453ef65e21 · inbound

A "Neural" Riemann solver for Relativistic Hydrodynamics cites this paper.

A "Neural" Riemann solver for Relativistic Hydrodynamics AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 17

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Observation 96d7b8f8-2d7f-4960-b720-3033f7a6efdd · inbound

Diffusion-Based Symbolic Regression cites this paper.

Diffusion-Based Symbolic Regression AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 27

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Observation db4a034c-6724-46c2-849e-859cbf3587c6 · inbound

Toward Supporting Narrative-Driven Data Exploration: Barriers and Design Opportunities cites this paper.

Toward Supporting Narrative-Driven Data Exploration: Barriers and Design Opportunities AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 3

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Observation 5b6fbd45-27e5-4e61-b25b-41198924394a · inbound

Data-driven discovery of dynamical models in biology cites this paper.

Data-driven discovery of dynamical models in biology AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 103

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Observation 1fb0879b-fa90-4f1c-8df0-5897706aa3cf · inbound

SABER: Symbolic Regression-based Angle of Arrival and Beam Pattern Estimator cites this paper.

SABER: Symbolic Regression-based Angle of Arrival and Beam Pattern Estimator AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 37

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Observation fd8a4f34-7a4d-4c36-bece-5ac3a9d722f2 · inbound

A First Observational Assessment of Cosmic Backreaction Over an Extended Redshift Range cites this paper.

A First Observational Assessment of Cosmic Backreaction Over an Extended Redshift Range AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:46:02.185083Z

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A First Observational Assessment of Cosmic Backreaction Over an Extended Redshift Range cites this paper.

A First Observational Assessment of Cosmic Backreaction Over an Extended Redshift Range AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 42

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Observation b526882a-58c9-4926-84a8-15dbb034a819 · inbound

Solving Physics Olympiad via Reinforcement Learning on Physics Simulators cites this paper.

Solving Physics Olympiad via Reinforcement Learning on Physics Simulators AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 2

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Observation 49fe356b-57a3-479a-a6fa-6efe9135a7ee · inbound

Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis cites this paper.

Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-05-20T15:43:26.391836Z

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Observation 431e5d70-813c-440c-96f2-ebfdd940e41f · inbound

Predicting intermediate-mass black hole formation in star clusters with machine learning cites this paper.

Predicting intermediate-mass black hole formation in star clusters with machine learning AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 83

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T09:21:20.979910Z

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Observation f0b192e2-a336-4024-9ea5-e234f4c97034 · inbound

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits cites this paper.

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T05:04:37.279687Z

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Observation 6251535b-b5ea-49e2-8300-b77f16e74821 · inbound

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models cites this paper.

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:47:30.208756Z

Source-reported events for the cited work

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Observation 989fd90f-fabe-4f2c-b175-f6f87bd0eb72 · inbound

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models cites this paper.

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T12:05:37.989430Z

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Observation ee0224da-31a2-4af9-80c3-d1306495c442 · inbound

Centauric 1-Jettiness in DIS and Universal Power Corrections cites this paper.

Centauric 1-Jettiness in DIS and Universal Power Corrections AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-07-04T05:09:35.440634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 578ae325-5a95-44f6-89a4-74c8102ab45d · inbound

Sample Complexity of Scientific Discovery: PAC Learnability of Compositional Function Trees cites this paper.

Sample Complexity of Scientific Discovery: PAC Learnability of Compositional Function Trees AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:54:21.877790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0c5546cb-946e-47f9-8820-929390670e8f · inbound

Inverse-k Primordial Oscillations from a Symbolic Regression Search cites this paper.

Inverse-k Primordial Oscillations from a Symbolic Regression Search AI Feynman: a Physics-Inspired Method for Symbolic Regression

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-11T11:22:54.456972Z

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