Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:19:09.442421Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2501.10339.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:19:09.442421Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:19:09.045006Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T20:46:51.734802Z
55 of 55 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8ec975ce-3929-4be6-8087-f912b22c696e · outbound
Principled model selection for stochastic dynamics Principled model selection for stochastic dynamics
Reference 1
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Observation 0c35f73f-0b5e-4cd0-aad6-f03547c1bde2 · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 2
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Observation ed697178-d7e3-4de4-85ec-167f3bfa61bb · outbound
Reference 3
Source-reported events for the cited work
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Observation 7d62f369-dd12-48ac-b06c-0dfdd08865e4 · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 4
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Observation 18fd951f-a836-4b69-a6c4-1e624fc0e339 · outbound
Principled model selection for stochastic dynamics Schmidt and H
Reference 5
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Observation 66913dd3-9ce0-49cc-890a-f4c4e1b0036b · outbound
Principled model selection for stochastic dynamics Discovering Symbolic Models from Deep Learning with Inductive Biases
Reference 6
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Observation 096d84d9-c7a4-47c4-9186-40fc5bd08533 · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 7
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Observation 5893065d-4de9-49be-ba8e-611287102647 · outbound
Principled model selection for stochastic dynamics Champion, P
Reference 8
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Principled model selection for stochastic dynamics Boninsegna, F
Reference 9
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Observation b8647319-fa25-4a65-a609-655fd6511702 · outbound
Principled model selection for stochastic dynamics Gao and G
Reference 10
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 11
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Reference 12
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Principled model selection for stochastic dynamics Nabeel, A
Reference 13
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Principled model selection for stochastic dynamics Frishman and P
Reference 14
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 15
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Principled model selection for stochastic dynamics Siegert, R
Reference 16
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Observation 4569bb57-4dd6-49c3-8534-da7350dda378 · outbound
Principled model selection for stochastic dynamics Risken, The Fokker-Planck Equation: Methods of So- lution and Applications, edited by H
Reference 17
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Observation acf53b18-7bb6-416a-9995-8dbb8ea9377c · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 18
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Observation b46e26e5-b602-4aa7-b90c-fa9d0761b44c · outbound
Principled model selection for stochastic dynamics Akaike, A new look at the statistical model identifica- tion, IEEE Transactions on Automatic Control 19, 716 (1974)
Reference 19
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Observation 5e382ea9-cfde-4968-88b2-79957920cbd4 · outbound
Principled model selection for stochastic dynamics Lebarbier and T
Reference 20
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Observation a48c752f-d230-45a0-b3c0-e2df7514db35 · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 21
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Observation fc9ad4be-c3a9-4fb9-9ae1-7cf35067ad97 · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 22
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Observation eae74992-544b-4b58-8806-d521d2b175fd · outbound
Principled model selection for stochastic dynamics Schwarz, Estimating the Dimension of a Model, The Annals of Statistics 6, 461 (1978), 2958889
Reference 23
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Reference 24
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 25
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 26
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Reference 27
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Observation 91dee5d4-e790-4f0a-b506-96c12da72850 · outbound
Principled model selection for stochastic dynamics Wanner and I
Reference 28
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Observation 2810b234-09c3-4dc8-9e57-7bc662fe68ad · outbound
Principled model selection for stochastic dynamics Unresolved cited work
Reference 29
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Observation de67f5a2-df1a-4762-b5b9-9c454b1cb6e0 · outbound
Reference 30
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Observation 3894c258-250d-4ba3-9ff8-47e04108455f · outbound
Principled model selection for stochastic dynamics Tibshirani, Regression Shrinkage and Selection Via the Lasso, Journal of the Royal Statistical Society Series B: Statistical Methodology 58, 267 (1996)
Reference 31
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Observation 03f1e18f-47ee-4f75-bddf-566ad6a5881c · outbound
Principled model selection for stochastic dynamics Ben Mhenni, S
Reference 32
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 33
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 34
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Principled model selection for stochastic dynamics Chen and Z
Reference 35
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 36
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 37
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Observation 712d3a98-4f29-4616-820a-774846d506d0 · outbound
Principled model selection for stochastic dynamics The code used to produce the data and figures of this article is available at github.com/odannis/PASTIS_paper
Reference 38
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 39
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Principled model selection for stochastic dynamics Ferretti, V
Reference 40
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Observation ec87f49f-cf1e-47e9-af3b-3f78432d090c · outbound
Principled model selection for stochastic dynamics Rish and G
Reference 41
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 42
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Principled model selection for stochastic dynamics Gross and O
Reference 43
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Principled model selection for stochastic dynamics Vitells and E
Reference 44
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Observation fd157bea-4864-45eb-bd7a-d1cec91ba9ab · outbound
Principled model selection for stochastic dynamics 6 connecting the inference error E(ˆFB) to the estimated log-likelihood L(X|ˆFB)
Reference 45
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Principled model selection for stochastic dynamics look-elsewhere effect
Reference 46
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Observation 637cd0f7-747e-4c77-adb0-772a44229ce3 · outbound
Principled model selection for stochastic dynamics 9), is the probability of selecting a model with one superflu- ous term which can be written as P[maxs IPASTIS(B∗ + {s}) > IPASTIS(B∗)] ≈ p
Reference 47
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Principled model selection for stochastic dynamics We derive here modified estimators discussed in the main text and presented in Fig
Reference 48
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Principled model selection for stochastic dynamics Unresolved cited work
Reference 49
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Principled model selection for stochastic dynamics For the prediction error in Fig
Reference 50
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Principled model selection for stochastic dynamics 3, allows comparison of models in a Bayesian framework without having to select any particular prior Π B(F B 1 ,
Reference 51
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Principled model selection for stochastic dynamics We note that it is primarily designed for ordinary differential equation inference, in the absence of dynamical noise
Reference 52
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Observation bf2eb3bf-f4a9-4b62-8a2e-be360654a696 · outbound
Principled model selection for stochastic dynamics The trajectory was divided into 7 segments of equal length
Reference 53
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Principled model selection for stochastic dynamics The LASSO regression itself was performed using the Lasso optimizer from the sklearn.linear model module in Scikit-learn
Reference 54
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Principled model selection for stochastic dynamics S2, the comparisons in the main text (Fig
Reference 55
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Observation 8ec975ce-3929-4be6-8087-f912b22c696e · inbound
Principled model selection for stochastic dynamics Principled model selection for stochastic dynamics
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Stoch-IDENT: New Method and Mathematical Analysis for Identifying SPDEs from Data Principled model selection for stochastic dynamics
Reference 27
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