Paper Citation Record · LEDGER

Active Learning for Neural PDE Solvers

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.01536.

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

pith.paper-citation-record.v1
2408.01536 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T20:19:20.633657Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7a59a57d-2549-4f52-b465-30dbf4120970 · inbound

Active Learning with Selective Time-Step Acquisition for PDEs cites this paper.

Active Learning with Selective Time-Step Acquisition for PDEs Active Learning for Neural PDE Solvers

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:54:08.569719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 69272800-f8fc-499c-8378-eda0fa81641e · inbound

Active learning with physics-informed neural networks for optimal sensor placement in deep tunneling through transversely isotropic elastic rocks cites this paper.

Active learning with physics-informed neural networks for optimal sensor placement in deep tunneling through transversely isotropic elastic rocks Active Learning for Neural PDE Solvers

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T20:19:20.633657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96231a4d-1332-4c23-b151-6c59256a45fd · inbound

Neural Operator Representation of Granular Micromechanics-based Failure Envelope cites this paper.

Neural Operator Representation of Granular Micromechanics-based Failure Envelope Active Learning for Neural PDE Solvers

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:21:14.256852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 92831881-311e-4ba0-ace5-803ddcf617ce · inbound

Data-Efficient Neural Operator Training via Physics-Based Active Learning cites this paper.

Data-Efficient Neural Operator Training via Physics-Based Active Learning Active Learning for Neural PDE Solvers

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.513218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d2feea59-ccba-4aa9-a954-5c2f3039369f · inbound

Data-Efficient Neural Operator Training via Physics-Based Active Learning cites this paper.

Data-Efficient Neural Operator Training via Physics-Based Active Learning Active Learning for Neural PDE Solvers

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.097837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7bc96fd0-171b-4f3d-ba69-4567fcb026a2 · inbound

Is Zero-Shot Super-Resolution Possible in Operator Learning? cites this paper.

Is Zero-Shot Super-Resolution Possible in Operator Learning? Active Learning for Neural PDE Solvers

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:52:35.025486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9cc48219-df86-4c0b-8b00-1a9654e7495d · inbound

No Free Lunch in Flow Surrogates under Time-Varying Boundary Conditions: A Two-Regime Study cites this paper.

No Free Lunch in Flow Surrogates under Time-Varying Boundary Conditions: A Two-Regime Study Active Learning for Neural PDE Solvers

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-30T16:23:26.954959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.