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Paper Citation Record · LEDGER

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.03000.

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

pith.paper-citation-record.v1
2607.03000 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T05:32:58.652553Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

18 of 18 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1528f5ef-60a9-4fb5-94ad-d5a653246527 · outbound

This paper cites Modeling of vehicle dynamics from real vehicle measurements using a neural network with two-stage hybrid learning for accurate long-term prediction,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Modeling of vehicle dynamics from real vehicle measurements using a neural network with two-stage hybrid learning for accurate long-term prediction,

Reference 1

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Observation 6804dd21-1263-4799-9b02-73ce574a15d0 · outbound

This paper cites Neural network vehicle models for high-performance automated driving,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Neural network vehicle models for high-performance automated driving,

Reference 2

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Observation a5395d6e-985c-467f-ae30-a33af6404bd2 · outbound

This paper cites Deep-neural-network-based modelling of longitudinal-lateral dynamics to predict the vehicle states for autonomous driving,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Deep-neural-network-based modelling of longitudinal-lateral dynamics to predict the vehicle states for autonomous driving,

Reference 3

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Observation 72d6f158-df3c-4a70-ae3d-7435f0d584a4 · outbound

This paper cites Data-driven vehicle dynam- ics: Neural network modeling for system identification and prediction in driver assistance control,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Data-driven vehicle dynam- ics: Neural network modeling for system identification and prediction in driver assistance control,

Reference 4

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:54698f4fafb58124a90a7032017474f5aca2a8db52f6478203c54d6e399d544a

Observation ce210f64-56f4-4b8a-b2f3-59324047addb · outbound

This paper cites Neural ordinary differential equations,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Neural ordinary differential equations,

Reference 5

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:055801d871e7423817545d3a092db42348b699dbd7b2bbf6861e825c2655c8c1

Observation 6b8f6315-5dd6-42b5-ad57-7db9c08d699c · outbound

This paper cites Learning nonlinear state-space models using autoencoders,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Learning nonlinear state-space models using autoencoders,

Reference 6

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:d890c64f540747ca73c28220ed7eed700d010ace290ec08f6061b36239870e45

Observation 262b710d-1704-4320-938a-8f9f4914ee56 · outbound

This paper cites Continuous-time system identification with neural networks: Model structures and fitting criteria,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Continuous-time system identification with neural networks: Model structures and fitting criteria,

Reference 7

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Observation 346a4304-3cbb-4e3e-8112-06f5883309d9 · outbound

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

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 8

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:efa2e0ab7fad9b7c810684baa9120c8a3780e3423f5aa612ca98e1f8f9b0d91b

Observation ca90f2d8-e7b7-4288-828e-043f5e8f263c · outbound

This paper cites Deep dynamics: Vehicle dynamics modeling with a physics-constrained neural network for autonomous racing,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Deep dynamics: Vehicle dynamics modeling with a physics-constrained neural network for autonomous racing,

Reference 9

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:3ca178b21890d3fb2aac5a6189b001f5e220f54177af85fc8853836d31c2cdc3

Observation 7dfa7ed3-d4f7-4d5f-837c-1404bc00723d · outbound

This paper cites Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction

Reference 11

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Observation 46c523b3-41bb-4488-9ceb-b8ad58ce40f1 · outbound

This paper cites Path planning for autonomous vehicles in unknown semi-structured environments,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Path planning for autonomous vehicles in unknown semi-structured environments,

Reference 12

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Observation 0b8b7bae-6690-4cd8-a6f1-b00eab63daf9 · outbound

This paper cites Trajectory planning for autonomous valet parking in narrow environments with enhanced hybrid A* search and nonlinear optimization,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Trajectory planning for autonomous valet parking in narrow environments with enhanced hybrid A* search and nonlinear optimization,

Reference 13

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Observation b38450e4-b15d-4f1c-bebe-98ae3c40aff3 · outbound

This paper cites Long short-term memory,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Long short-term memory,

Reference 14

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:edba121f2b6fbd7eef6338a3316305c6e892d4033d6063fdfafefdb6cf0a6c55

Observation 13d6b2e6-291f-4d33-9d19-bc37d093b109 · outbound

This paper cites Nonlinear black-box modeling in system identification: A unified overview,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Nonlinear black-box modeling in system identification: A unified overview,

Reference 15

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:8c992dfce8dd54c74bd72967386797407c5ead432831f8d93238a7b75ef27502

Observation ea9cc55c-cefc-4b09-896c-5e15f7b1cdc0 · outbound

This paper cites Learning phrase representations using RNN encoder– decoder for statistical machine translation,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Learning phrase representations using RNN encoder– decoder for statistical machine translation,

Reference 16

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Observation 6afc8757-8edb-401f-9027-a1d1a2fa0981 · outbound

This paper cites Optimal paths for a car that goes both forwards and backwards,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Optimal paths for a car that goes both forwards and backwards,

Reference 17

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Observation 19b24096-c132-4f58-a1bb-a99f7bffe4e7 · outbound

This paper cites Optimization-based collision avoidance,.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation Optimization-based collision avoidance,

Reference 18

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source=pdf_text observed=2026-07-12T05:32:58.652553Z digest=sha256:f18637956809254bd73fa96e2f7809dd2392404a891cb32db0a25d05a81de424

Observation d791fe95-5f01-4008-bafa-a6fbadd3ed14 · outbound

This paper cites The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?.

Physics-Informed Neural State-Space Modeling of Battery-Electric Vehicle Dynamics for Closed-Loop Automated Parking Simulation The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?

Reference 19

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Pith citing papers

No inbound Pith citation observations are available.