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Paper Citation Record · LEDGER

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling

As of 22 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2607.09136.

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

pith.paper-citation-record.v1
2607.09136 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T05:09:45.335938Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

10 of 10 outbound references displayed

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  • verified fuzzy0
  • unresolved9
  • parse uncertain0
  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d61d0c63-40c0-4101-a41d-13945e694cb0 · outbound

This paper cites Design Principles for Energy-Efficient Legged Locomo- tion and Implementation on the MIT Cheetah Robot,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Design Principles for Energy-Efficient Legged Locomo- tion and Implementation on the MIT Cheetah Robot,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1f8337fe-7b5a-4022-9a12-b31730bb90a6 · outbound

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

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 2

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unresolved
no resolver link, observed 2026-07-13T05:09:45.335938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8f3f62d0-d96f-47e2-bae5-9510e03a0bf6 · outbound

This paper cites Physics-informed machine learning,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Physics-informed machine learning,

Reference 3

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unresolved
no resolver link, observed 2026-07-13T05:09:45.335938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T05:09:45.335938Z digest=sha256:3601bfb11e5edb0115e3cfa5ab8e72f7f675de947263c063d4042dfe835cc9fa

Observation ee2d96db-4321-4eaf-9323-993db626d58d · outbound

This paper cites Deep Residual Learning for Image Recognition,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Deep Residual Learning for Image Recognition,

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T05:09:45.335938Z digest=sha256:732a94df69a37f7177608d0fcb9e452a4be5631fe0c8101c0410fbea69e9b1d2

Observation 3687d9d9-0ce1-4e0e-93dd-d8de063e855e · outbound

This paper cites When and why PINNs fail to train: A neural tangent kernel perspective,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling When and why PINNs fail to train: A neural tangent kernel perspective,

Reference 5

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unresolved
no resolver link, observed 2026-07-13T05:09:45.335938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T05:09:45.335938Z digest=sha256:377a5b947529db82c52e51b9f96922b488a86fa121334e87d479c2f8acca3e56

Observation 9288f124-3de0-4e0d-be2d-43f20010b043 · outbound

This paper cites Adam: A Method for Stochastic Optimization,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Adam: A Method for Stochastic Optimization,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 860c1f6e-43b7-4556-ad31-fbf24daf6339 · outbound

This paper cites Real-time deep learning-based model predictive control of a 3-DOF biped robot leg,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Real-time deep learning-based model predictive control of a 3-DOF biped robot leg,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f8b65b1c-0b48-4259-820d-56c637c514a5 · outbound

This paper cites Real-time trajectory tracking and stabilization of quadro- tors using deep Koopman-based model predictive control,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Real-time trajectory tracking and stabilization of quadro- tors using deep Koopman-based model predictive control,

Reference 8

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 421d6b66-d5c9-4a05-9a3f-86983ddca1be · outbound

This paper cites Physics- informed neural network: principles and applications,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling Physics- informed neural network: principles and applications,

Reference 9

Resolution
malformed identifier
doi_truncated, observed 2026-07-13T05:19:25.914454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-13T05:09:45.335938Z digest=sha256:a186ac60348b092c645ae8e98eaccf8d9ccd11acc4be5a2648b7f1b4fdaf3959

Observation 4d3ee48c-3490-4bc4-bf95-871056b56d5a · outbound

This paper cites A PINN-Based Nonlinear PMSM Electromagnetic Model Using Differential Inductance Theory,.

Residual Physics-Informed Neural Networks for High-Fidelity BLDC Motor Modeling A PINN-Based Nonlinear PMSM Electromagnetic Model Using Differential Inductance Theory,

Reference 10

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T05:09:45.335938Z digest=sha256:4bd60448def944fb37dbfe22daa1ba9d64bad7bbe55a688dc757582bbb66623b

Pith citing papers

No inbound Pith citation observations are available.