Paper Citation Record · LEDGER

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction

As of 11 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.00353.

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

pith.paper-citation-record.v1
2507.00353 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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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

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation 527d8e33-c2b5-4c11-83e1-36a588c4490f · outbound

This paper cites Batteries and fuel cells for emerging electric vehicle markets,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Batteries and fuel cells for emerging electric vehicle markets,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:28.655034Z

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Observation d6b0cc0b-d654-4a28-8246-f384755e2b22 · outbound

This paper cites A review of lithium-ion battery for electric vehicle applications and beyond,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A review of lithium-ion battery for electric vehicle applications and beyond,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:28.399321Z

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Observation 1ba68989-7e6b-4d53-806f-f61ee0d20a43 · outbound

This paper cites A comparison between physics-based li-ion battery models,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A comparison between physics-based li-ion battery models,

Reference 3

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Observation 735cb195-5735-409c-919e-e6b48c578e3a · outbound

This paper cites Lithium-ion battery multi-scale modeling coupled with simplified electrochemical model and kinetic monte carlo model,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Lithium-ion battery multi-scale modeling coupled with simplified electrochemical model and kinetic monte carlo model,

Reference 4

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Observation f9f87093-f93d-4ad6-90f0-b41a4f42912a · outbound

This paper cites Modeling of li-ion cells for fast simulation of high c-rate and low temperature operations,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Modeling of li-ion cells for fast simulation of high c-rate and low temperature operations,

Reference 5

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Observation 1404367f-b2d5-48dd-90db-be4f7a45f1f8 · outbound

This paper cites New data optimization framework for parameter estimation under uncertainties with application to lithium-ion battery,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction New data optimization framework for parameter estimation under uncertainties with application to lithium-ion battery,

Reference 6

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Observation a15e73b6-6e1a-4d06-b656-e01fd4392fa0 · outbound

This paper cites Reinforcement learning of optimal input excitation for parameter estimation with application to li-ion battery,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Reinforcement learning of optimal input excitation for parameter estimation with application to li-ion battery,

Reference 7

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Observation 508360a2-5a82-47d0-a7bd-dac04cbadaa4 · outbound

This paper cites Real-Time Optimal Design of Experiment for Parameter Identification of Li-Ion Cell Electrochemical Model.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Real-Time Optimal Design of Experiment for Parameter Identification of Li-Ion Cell Electrochemical Model

Reference 8

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Observation 653109b1-e896-4dee-89b3-fe1803a377b6 · outbound

This paper cites A comparative study between physics, electrical and data driven lithium-ion battery voltage modeling approaches,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A comparative study between physics, electrical and data driven lithium-ion battery voltage modeling approaches,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:26.900541Z

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Observation f8ff237d-0d81-4ecb-8f5a-0fb4fbd05a3b · outbound

This paper cites Particle swarm optimization of elman neural network applied to battery state of charge and state of health estimation,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Particle swarm optimization of elman neural network applied to battery state of charge and state of health estimation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:26.679738Z

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Observation b4d680e4-a051-4c78-a8b2-b935d8162830 · outbound

This paper cites Lithium- ion battery digitalization: Combining physics-based models and machine learning,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Lithium- ion battery digitalization: Combining physics-based models and machine learning,

Reference 11

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Observation e74ddbdd-2047-4659-8db3-c68d0335dbc7 · outbound

This paper cites Combining physics-based and machine learn- ing methods to accelerate innovation in sustainable transportation and beyond: a control perspective,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Combining physics-based and machine learn- ing methods to accelerate innovation in sustainable transportation and beyond: a control perspective,

Reference 12

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Observation 25047a05-3cf8-4610-9407-bd781fa41895 · outbound

This paper cites Integrating physics-based modeling with machine learning for lithium-ion batteries,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Integrating physics-based modeling with machine learning for lithium-ion batteries,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:25.994542Z

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Observation 6218707d-5bd9-4eb6-a15b-cafc38d5a93a · outbound

This paper cites Dynamic models of li-ion batteries for diagnosis and operation: a review and perspective,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Dynamic models of li-ion batteries for diagnosis and operation: a review and perspective,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:25.728159Z

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Observation ff22c5b1-d31a-4e40-9203-8d71804c3692 · outbound

This paper cites Discovery of physics from data: Universal laws and discrepancies,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Discovery of physics from data: Universal laws and discrepancies,

Reference 15

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Observation 40cea492-5359-42d0-9e0c-bf5291a9e9ed · outbound

This paper cites Discovering a reaction–diffusion model for alzheimer’s disease by combining pinns with symbolic regression,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Discovering a reaction–diffusion model for alzheimer’s disease by combining pinns with symbolic regression,

Reference 16

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Observation 044d3115-ac71-4c1b-be8c-71811b434d33 · outbound

This paper cites Sindy-crn: Sparse identification of chemical reaction networks from data,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Sindy-crn: Sparse identification of chemical reaction networks from data,

Reference 17

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Observation a3f060b7-4714-478b-ac22-826727a36c07 · outbound

This paper cites A data-driven frame- work for learning governing equations of li-ion batteries and co- estimating voltage and state-of-charge,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A data-driven frame- work for learning governing equations of li-ion batteries and co- estimating voltage and state-of-charge,

Reference 18

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Observation 510e224e-b8b2-4d61-8421-69498c98ef5c · outbound

This paper cites Data-driven battery modeling based on koopman operator approximation using neural network,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Data-driven battery modeling based on koopman operator approximation using neural network,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:24.706113Z

Source-reported events for the cited work

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Observation abde310e-2680-407e-a047-c9b02813337e · outbound

This paper cites Learning the laws of lithium-ion transport in electrolytes using symbolic regression,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Learning the laws of lithium-ion transport in electrolytes using symbolic regression,

Reference 20

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Observation b2b0c2e1-959a-4673-9a30-83ab8ea02cf1 · outbound

This paper cites A computational framework for physics-informed symbolic regression with straightforward integra- tion of domain knowledge,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A computational framework for physics-informed symbolic regression with straightforward integra- tion of domain knowledge,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:24.358969Z

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Observation 488d4ae6-9a72-460a-aa49-e768b668666a · outbound

This paper cites Improving Low-Fidelity Models of Li-ion Batteries via Hybrid Sparse Identification of Nonlinear Dynamics.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Improving Low-Fidelity Models of Li-ion Batteries via Hybrid Sparse Identification of Nonlinear Dynamics

Reference 22

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Observation e3d5bd89-408e-431a-bdb0-e8c1d7d2d0b3 · outbound

This paper cites Bagging, optimized dynamic mode decomposition for robust, stable forecasting with spatial and temporal uncertainty quantification,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Bagging, optimized dynamic mode decomposition for robust, stable forecasting with spatial and temporal uncertainty quantification,

Reference 23

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Observation 23639cde-d284-4580-9911-68fd45f13c71 · outbound

This paper cites Battery state-of-charge estimation using data-driven gaussian process kalman filters,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Battery state-of-charge estimation using data-driven gaussian process kalman filters,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:23.992827Z

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Observation a8aed09b-ba80-449c-981e-d849c1b43aba · outbound

This paper cites A novel gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A novel gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:23.847933Z

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Observation c1646cce-84d2-4edc-a2b1-b0fbc57f438b · outbound

This paper cites V ovk, A.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction V ovk, A

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:23.630134Z

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Observation 6bc428d6-74a9-442f-9521-b02d0f5a0626 · outbound

This paper cites Manokhin, Practical Guide to Applied Conformal Prediction in Python.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Manokhin, Practical Guide to Applied Conformal Prediction in Python

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:23.466613Z

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Observation 5c90e8c5-1db8-4ad3-aea5-0e7cfe7232ed · outbound

This paper cites A reduced-order electrochemical model of li-ion batteries for control and estimation applications,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction A reduced-order electrochemical model of li-ion batteries for control and estimation applications,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:23.339863Z

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Observation edc38027-d19a-41f6-a151-ba7166ce8455 · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynamical systems,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Discovering governing equations from data by sparse identification of nonlinear dynamical systems,

Reference 29

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Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Sparse identification of nonlinear dynamics for rapid model recovery,

Reference 30

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Observation b9ba1a6f-5ea5-4e43-9409-f614ec6457e0 · outbound

This paper cites Scaled-cPIKANs: Domain Scaling in Chebyshev-based Physics-informed Kolmogorov-Arnold Networks.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Scaled-cPIKANs: Domain Scaling in Chebyshev-based Physics-informed Kolmogorov-Arnold Networks

Reference 31

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This paper cites Data-driven identi- fication of parametric partial differential equations,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Data-driven identi- fication of parametric partial differential equations,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:23.056681Z

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Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Unresolved cited work

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This paper cites Ensemble- sindy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Ensemble- sindy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control,

Reference 34

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Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Hastie, R

Reference 35

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Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Stability selection,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:22.748527Z

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Observation b3ffdc59-547a-4bde-b96b-bffb74134979 · outbound

This paper cites Conformal prediction with neural networks,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Conformal prediction with neural networks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:22.641632Z

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Observation e59486e7-1969-4f39-a88d-c9bfc0eb30d2 · outbound

This paper cites Sequential predictive conformal inference for time series,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Sequential predictive conformal inference for time series,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:22.509258Z

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Observation 20ffe33d-5234-4a83-9137-fc721a9c2107 · outbound

This paper cites Conformal prediction interval for dynamic time-series,.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Conformal prediction interval for dynamic time-series,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:22.379558Z

Source-reported events for the cited work

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Observation f9ea0d95-377f-4400-9b1f-354315294e49 · outbound

This paper cites Quantile regression forests.

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction Quantile regression forests

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:23:22.260647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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