Paper Citation Record · LEDGER

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies

As of 10 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2507.15259.

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

pith.paper-citation-record.v1
2507.15259 v1

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:40:17.019627Z

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

8 of 8 outbound references displayed

verified exact1
verified fuzzy5
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb2da168-c306-4466-bbc1-b82f935c4ff4 · outbound

This paper cites UNIFI specifications for grid-forming inverter-based resources (Version 2),.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies UNIFI specifications for grid-forming inverter-based resources (Version 2),

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:17.966772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 784aef83-dfb0-48e9-b17a-72df559ba7e7 · outbound

This paper cites Generative adversarial nets,.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies Generative adversarial nets,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:17.829843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d583453c-d5fd-445d-a001-d8c7f6e23963 · outbound

This paper cites Physics-informed neural networks: A deep learn- ing framework for solving forward and inverse problems involving nonlinear partial differential equations,.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies Physics-informed neural networks: A deep learn- ing framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:17.662772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 44bda7b4-83bf-438d-97b6-0f73eb43298d · outbound

This paper cites Coherency-Aware Learning Control of Inverter-Dominated Grids: A Distributed Risk-Constrained Approach,.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies Coherency-Aware Learning Control of Inverter-Dominated Grids: A Distributed Risk-Constrained Approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:17.506692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 28d68f62-6d9d-476a-ba2a-6bc1a8615548 · outbound

This paper cites Model specification of droop-controlled, grid-forming inverters (REGFM_A1),.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies Model specification of droop-controlled, grid-forming inverters (REGFM_A1),

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:40:17.349550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9055f2ff-e774-4ea9-a079-0a112057e454 · outbound

This paper cites On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:40:17.193865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4c7df574-7dd4-4029-9d4f-f6ce08f8103f · outbound

This paper cites Latent ODEs for Irregularly-Sampled Time Series.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies Latent ODEs for Irregularly-Sampled Time Series

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:16.944662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c36e132-70eb-4116-9088-3306ad3ee01a · outbound

This paper cites Neural Ordinary Differential Equations.

Physics-Informed Learning of Proprietary Inverter Models for Grid Dynamic Studies Neural Ordinary Differential Equations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T15:40:17.019627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.