Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2403.02913.
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
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T21:53:31.172306Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation e2c02989-8b21-4fc8-9d8b-08b5d52a9d73 · inbound
Symbolic Regression of Data-Driven Reduced Order Model Closures for Under-Resolved, Convection-Dominated Flows Scientific machine learning for closure models in multiscale problems: a review
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8066e7e7-7d03-46a6-bd2d-4fae9661b5bb · inbound
FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models Scientific machine learning for closure models in multiscale problems: a review
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b5cd7c7-5d64-4fb7-ab12-6ab290d82cde · inbound
Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network Scientific machine learning for closure models in multiscale problems: a review
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 234fc238-48a8-4bd4-a610-b8f7d23f9e23 · inbound
Locally Adaptive Conformal Inference for Operator Models Scientific machine learning for closure models in multiscale problems: a review
Reference 2019
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3c7947c-358a-4d1a-a65d-84bef18f678b · inbound
Multiscale Physics-Informed Neural Network for Complex Fluid Flows with Long-Range Dependencies Scientific machine learning for closure models in multiscale problems: a review
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4a84ca8d-ee1f-4b8d-ad9f-2c4a04cc0f34 · inbound
A meshfree exterior calculus for generalizable and data-efficient learning of physics from point clouds Scientific machine learning for closure models in multiscale problems: a review
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dab05810-78a7-40b4-9a02-d55ff448c0ac · inbound
Wavelet Flow Matching for Multi-Scale Physics Emulation Scientific machine learning for closure models in multiscale problems: a review
Reference 51
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7cfcbba1-f103-4113-83d4-74986150d573 · inbound
Hybrid Neural Ordinary Differential Equations for Data-Efficient Polymerization Modeling with Incomplete Kinetics Scientific machine learning for closure models in multiscale problems: a review
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 5200b68a-9303-4503-8673-da1f70e03ed0 · inbound
Generalized Forcing Method: Generation of Diverse Data for Training Linear Transport PDE Closure Models Scientific machine learning for closure models in multiscale problems: a review
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0b4bd3a4-b462-4249-a458-3179e2faa287 · inbound
Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows Scientific machine learning for closure models in multiscale problems: a review
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f2039aa4-71d7-431a-8a6d-5197b6e0476e · inbound
Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics Scientific machine learning for closure models in multiscale problems: a review
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0c471c75-4758-4b80-a588-7dca0b860104 · inbound
Why Does the Future Branch? Identifiable Closure Tests for Stochastic Physical World Models Scientific machine learning for closure models in multiscale problems: a review
Reference 38
Source-reported events for the cited work
Unavailable: canonical work link unavailable.