Paper Citation Record · LEDGER

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests

As of 9 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2509.19710.

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

pith.paper-citation-record.v1
2509.19710 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:38:34.145477Z

measured 16 of 16 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T02:30:41.818145Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:06:55.950605Z

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5c1b3c21-1447-4338-875e-68f07e9fb9c4 · outbound

This paper cites An Approach to Symbolic Regression Using Feyn.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests An Approach to Symbolic Regression Using Feyn

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:31.978584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07058d30-5b20-48d6-ae19-3ad459a87ddf · outbound

This paper cites & Sedgewick, R.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests & Sedgewick, R

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:32.097325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da3c9c92-218e-4766-9702-56653720163c · outbound

This paper cites & Rubin, D.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests & Rubin, D

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:32.413329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 925f7538-e823-4fab-a481-27b5569850eb · outbound

This paper cites (1992), Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments, in ‘Bayesian Statistics’, Vol.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests (1992), Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments, in ‘Bayesian Statistics’, Vol

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:32.591808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b922c9c2-82f1-463f-99e9-73961e011f7e · outbound

This paper cites & van der Vaart, A.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests & van der Vaart, A

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:32.715318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a35ea91-e411-466a-99df-83696377402e · outbound

This paper cites an unresolved cited work.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:32.823883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e62a44d-07dd-44aa-8a09-67b54e3362ca · outbound

This paper cites an unresolved cited work.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:32.953355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db6c4f34-7ffc-4cd6-a050-ac1a4196af79 · outbound

This paper cites Bayesian Symbolic Regression.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Bayesian Symbolic Regression

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:33.145011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caa6fc42-867d-4731-9ccf-a14f3c7322dd · outbound

This paper cites an unresolved cited work.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:33.251174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67566189-dd6f-4366-a808-9472fd9bb875 · outbound

This paper cites Invariant Representation of Mathematical Expressions.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Invariant Representation of Mathematical Expressions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:33.354538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa87a79c-b967-4b08-b377-ea44340705f4 · outbound

This paper cites (1994), ‘Markov Chains for Exploring Posterior Distributions’, The Annals of Statistics 22(4).

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests (1994), ‘Markov Chains for Exploring Posterior Distributions’, The Annals of Statistics 22(4)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:33.555792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1b0c508-715d-4ac0-8d8d-d54491d52224 · outbound

This paper cites & Tegmark, M.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests & Tegmark, M

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:33.725942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49ba5ae2-5b7b-4ef7-824a-6e5510aa29a8 · outbound

This paper cites (2018), High-Dimensional Probability: An Introduction with Applications in Data Science , Cambridge University Press.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests (2018), High-Dimensional Probability: An Introduction with Applications in Data Science , Cambridge University Press

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:33.887466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7e5e632-8e1a-4a2c-9a41-dc4f14257b21 · outbound

This paper cites an unresolved cited work.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:34.023675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdf8d71b-146c-4f2e-b7bf-a05ccf20d6f5 · outbound

This paper cites an unresolved cited work.

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T15:38:34.145477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 2020b16b-9731-4ff9-a798-152d9210f5b1 · inbound

Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression cites this paper.

Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-28T01:21:33.520974Z

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.