Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T12:35:35.704997Z
Paper Citation Record · LEDGER
Exploring Multi-view Symbolic Regression methods in physical sciences
As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 2 inbound Pith citation observations for arXiv:2509.10500.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T12:11:28.043929Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z
Reference resolution
35 of 35 outbound references displayed
- verified exact7
- verified fuzzy11
- unresolved14
- parse uncertain0
- malformed identifier1
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 17649401-9f2a-4aed-80f6-8aa6f612ac42 · outbound
This paper cites 2020 Operon C++: An Efficient Genetic Programming Framework for Symbolic Regression.
Exploring Multi-view Symbolic Regression methods in physical sciences 2020 Operon C++: An Efficient Genetic Programming Framework for Symbolic Regression
Reference 1
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-05T12:35:36.386816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cf7b7eba-98e0-4d6b-b7a1-b434c59b7945 · outbound
This paper cites Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl.
Exploring Multi-view Symbolic Regression methods in physical sciences Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:33.965370Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b00aac3-25c0-4adb-ac66-20bef96a4c3a · outbound
This paper cites 2021 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients.
Exploring Multi-view Symbolic Regression methods in physical sciences 2021 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:38.118629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 11e25997-97a4-4038-9685-a2dfb46a02c5 · outbound
This paper cites 2023 Deep Symbolic Regression for Physics Guided by Units Constraints: Toward the Automated Discovery of Physical Laws.
Exploring Multi-view Symbolic Regression methods in physical sciences 2023 Deep Symbolic Regression for Physics Guided by Units Constraints: Toward the Automated Discovery of Physical Laws
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:34.146957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee52f492-771f-4e69-9a75-5dd1db00a266 · outbound
This paper cites an unresolved cited work.
Exploring Multi-view Symbolic Regression methods in physical sciences Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T12:35:37.843600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e411bab2-2fbb-4ac6-bba1-e8c0e43065ad · outbound
This paper cites Exhaustive Symbolic Regression.
Exploring Multi-view Symbolic Regression methods in physical sciences Exhaustive Symbolic Regression
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:34.272945Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5543742e-4241-4584-9b9e-efd9ce32b9dc · outbound
This paper cites syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy.
Exploring Multi-view Symbolic Regression methods in physical sciences syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:34.322190Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 363bd245-a382-4d49-8086-42c573bb2c62 · outbound
This paper cites 2019 Fast, accurate, and transferable many-body interatomic potentials by symbolic regression.
Exploring Multi-view Symbolic Regression methods in physical sciences 2019 Fast, accurate, and transferable many-body interatomic potentials by symbolic regression
Reference 9
- Resolution
- verified exact
- doi, observed 2026-08-05T12:35:35.989724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 846fa00c-7998-446a-8b57-4803a5c69035 · outbound
This paper cites 2023 A Flexible Symbolic Regression Method for Constructing Interpretable Clinical Prediction Models.
Exploring Multi-view Symbolic Regression methods in physical sciences 2023 A Flexible Symbolic Regression Method for Constructing Interpretable Clinical Prediction Models
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:34.459537Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59c28bb5-f3b7-425f-b6a8-4d92b5cff7d8 · outbound
This paper cites 2023 Understanding conflict origin and dynamics on Twitter: A real-time detection system.Expert Systems with Applications 212, 118748.
Exploring Multi-view Symbolic Regression methods in physical sciences 2023 Understanding conflict origin and dynamics on Twitter: A real-time detection system.Expert Systems with Applications 212, 118748
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:37.600757Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3903d7fd-0830-4896-8c1e-76453e49d3cc · outbound
This paper cites 2024 Data-Driven Equation Discovery of a Cloud Cover Parameterization.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 Data-Driven Equation Discovery of a Cloud Cover Parameterization
Reference 12
- Resolution
- verified exact
- raw_fallback, observed 2026-08-05T12:35:36.205477Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ba5d60d5-2866-499c-aed2-5b5576eeceb1 · outbound
This paper cites Multi-View Symbolic Regression.
Exploring Multi-view Symbolic Regression methods in physical sciences Multi-View Symbolic Regression
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T12:35:35.966406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 622d334c-774e-4b8e-9c03-d43ea4f65ea1 · outbound
This paper cites 2024 Class Symbolic Regression: Gotta Fit ’Em All.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 Class Symbolic Regression: Gotta Fit ’Em All
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:34.719660Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af407bc4-afed-4769-8444-22e8787b155b · outbound
This paper cites 2024 Machine learning mathematical models for incidence estimation during pandemics.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 Machine learning mathematical models for incidence estimation during pandemics
Reference 15
- Resolution
- verified exact
- doi, observed 2026-08-05T12:35:35.937742Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b11b1249-3723-4230-bb6c-a136ed2edcb9 · outbound
This paper cites 2018 Predicting friction system performance with symbolic regression and genetic programming with factor variables.
Exploring Multi-view Symbolic Regression methods in physical sciences 2018 Predicting friction system performance with symbolic regression and genetic programming with factor variables
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:37.424521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fd57189e-5b38-4d44-8463-827cb3701542 · outbound
This paper cites Contemporary Symbolic Regression Methods and their Relative Performance.
Exploring Multi-view Symbolic Regression methods in physical sciences Contemporary Symbolic Regression Methods and their Relative Performance
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:34.918092Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ba7a6ca-0c09-45b5-8d05-605fc8c83507 · outbound
This paper cites 2024 SRBench++: Principled benchmarking of symbolic regression with domain-expert interpretation.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 SRBench++: Principled benchmarking of symbolic regression with domain-expert interpretation
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:37.234143Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation edf84e28-50e4-4707-a54a-364dd1e8ad5b · outbound
This paper cites 2025 Call for Action: towards the next generation of symbolic regression benchmark.
Exploring Multi-view Symbolic Regression methods in physical sciences 2025 Call for Action: towards the next generation of symbolic regression benchmark
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:35.041663Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 357d7951-a0ff-4358-952e-da96d7c3c89f · outbound
This paper cites 2024 The Inefficiency of Genetic Programming for Symbolic Regression.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 The Inefficiency of Genetic Programming for Symbolic Regression
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:37.066608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8eb4185b-69b4-4a5a-ac95-ee58ed81a3af · outbound
This paper cites 2021 Egg: Fast and extensible equality saturation.
Exploring Multi-view Symbolic Regression methods in physical sciences 2021 Egg: Fast and extensible equality saturation
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:36.917612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2d1835e9-c08f-43ce-b3c4-32a179be2a50 · outbound
This paper cites Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery.
Exploring Multi-view Symbolic Regression methods in physical sciences Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:35.270599Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 844093fd-41b8-4570-ba2d-935c93e0c74f · outbound
This paper cites Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles.
Exploring Multi-view Symbolic Regression methods in physical sciences Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:35.367118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42b1c111-0b52-4710-a946-e27ff53c7b44 · outbound
This paper cites Dark Matter Halos around Galaxies.
Exploring Multi-view Symbolic Regression methods in physical sciences Dark Matter Halos around Galaxies
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T12:35:35.877315Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 14bb9a91-bc91-4b0f-a618-d7a26a0c22b4 · outbound
This paper cites 2020 Navarro-Frenk-White dark matter profile and the dark halos around disk systems.
Exploring Multi-view Symbolic Regression methods in physical sciences 2020 Navarro-Frenk-White dark matter profile and the dark halos around disk systems
Reference 25
- Resolution
- verified exact
- doi, observed 2026-08-05T12:35:35.857742Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e9466831-00cf-4344-bd9a-7091260e00ea · outbound
This paper cites 2011 The original Michaelis constant: translation of the 1913 Michaelis-Menten paper.
Exploring Multi-view Symbolic Regression methods in physical sciences 2011 The original Michaelis constant: translation of the 1913 Michaelis-Menten paper
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:36.763258Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 16c0e8e6-2e06-48bf-9114-e105cc725d54 · outbound
This paper cites 1933 Strömungsgestze in rauhen Rohren.
Exploring Multi-view Symbolic Regression methods in physical sciences 1933 Strömungsgestze in rauhen Rohren
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:36.608150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 698b35a5-d020-4db7-add4-f64e7076535d · outbound
This paper cites 2020 Bayesian Machine Scientist to Compare Data Collapses for the Nikuradse Dataset.
Exploring Multi-view Symbolic Regression methods in physical sciences 2020 Bayesian Machine Scientist to Compare Data Collapses for the Nikuradse Dataset
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:35.545399Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49c27454-17c1-409a-b909-0fd534898dae · outbound
This paper cites 2024 The Inefficiency of Genetic Programming for Symbolic Regression – Extended Version.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 The Inefficiency of Genetic Programming for Symbolic Regression – Extended Version
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:35.594787Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4221402-88c1-4fe9-ac92-ccbb2f0d0217 · outbound
This paper cites 2024 A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming.
Exploring Multi-view Symbolic Regression methods in physical sciences 2024 A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:36.474680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 27f2ce8d-f8bf-40dd-a6eb-61870dcec826 · outbound
This paper cites 1999 Emergence of scaling in random networks.
Exploring Multi-view Symbolic Regression methods in physical sciences 1999 Emergence of scaling in random networks
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:36.444039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 061da958-0bf0-4711-91b8-dc8168485a58 · outbound
This paper cites 2009 Power-law distributions in empirical data.
Exploring Multi-view Symbolic Regression methods in physical sciences 2009 Power-law distributions in empirical data
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T12:35:36.413282Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 82588a1b-db94-4fd5-8f67-ca63ec015417 · outbound
This paper cites Handbook of Network Analysis [KONECT -- the Koblenz Network Collection].
Exploring Multi-view Symbolic Regression methods in physical sciences Handbook of Network Analysis [KONECT -- the Koblenz Network Collection]
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T12:35:35.768292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7713c075-edb4-432b-8106-063f99caec51 · outbound
This paper cites 2009 The core-collapse rate from the Supernova Legacy Survey.
Exploring Multi-view Symbolic Regression methods in physical sciences 2009 The core-collapse rate from the Supernova Legacy Survey
Reference 34
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-05T12:35:35.697241Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e809c3cf-3e54-4dfc-8cb6-62f4ab91946a · outbound
This paper cites 2019 Supernova Photometric Classification Pipelines Trained on Spectroscopically Classified Supernovae from the Pan- STARRS1 Medium-deep Survey.The Astrophysical Journal 884, 83.
Exploring Multi-view Symbolic Regression methods in physical sciences 2019 Supernova Photometric Classification Pipelines Trained on Spectroscopically Classified Supernovae from the Pan- STARRS1 Medium-deep Survey.The Astrophysical Journal 884, 83
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:35:35.701174Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 79dfb4e6-8ea6-49bd-bf18-ef43e639942b · outbound
This paper cites 2025 rEGGression: an Interactive and Agnostic Tool for the Exploration of Symbolic Regression Models.
Exploring Multi-view Symbolic Regression methods in physical sciences 2025 rEGGression: an Interactive and Agnostic Tool for the Exploration of Symbolic Regression Models
Reference 36
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-05T12:35:36.290020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
Observation 4e21c32c-2db5-403f-8a7a-87974e6a03d5 · inbound
Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing cites this paper.
Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing Exploring Multi-view Symbolic Regression methods in physical sciences
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T12:11:28.043929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6161a22-47cc-4968-bc7c-bef19dc89f3b · inbound
Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations cites this paper.
Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations Exploring Multi-view Symbolic Regression methods in physical sciences
Reference 235
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T15:51:01.826146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.