Paper Citation Record · LEDGER

Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1710.11431.

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

pith.paper-citation-record.v1
1710.11431 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:22:42.931988Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T00:16:24.314197Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation eee2a3f8-dc17-419a-9376-eea9c2a47634 · inbound

Enforcing Analytic Constraints in Neural-Networks Emulating Physical Systems cites this paper.

Enforcing Analytic Constraints in Neural-Networks Emulating Physical Systems Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T05:38:38.729791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f86e8b9-db28-439b-a7ae-0aeb6b63bb71 · inbound

PDE-DKL: PDE-constrained deep kernel learning in high dimensionality cites this paper.

PDE-DKL: PDE-constrained deep kernel learning in high dimensionality Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T00:14:36.407463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57909540-0761-4b07-b9e9-3c508486c1f0 · inbound

Physics-Assisted and Topology-Informed Deep Learning for Weather Prediction cites this paper.

Physics-Assisted and Topology-Informed Deep Learning for Weather Prediction Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Reference 190

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:42.931988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b863ee7-1403-46e0-9bb0-054a49aa24b2 · inbound

Exploring Efficient Quantification of Modeling Uncertainties with Differentiable Physics-Informed Machine Learning Architectures cites this paper.

Exploring Efficient Quantification of Modeling Uncertainties with Differentiable Physics-Informed Machine Learning Architectures Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:00.126647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e207c92b-d938-43ec-b30d-59f92ba0127f · inbound

Data assimilation for energy-aware hybrid models cites this paper.

Data assimilation for energy-aware hybrid models Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T12:23:11.173707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff402622-661a-4d01-a444-e14ff5c9ac29 · inbound

Physics-Guided Recurrent State-Space Neural Networks for Multi-Step Prediction cites this paper.

Physics-Guided Recurrent State-Space Neural Networks for Multi-Step Prediction Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-02T00:16:24.316939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.