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Paper Citation Record · LEDGER

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models

As of 20 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2505.01666.

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

pith.paper-citation-record.v1
2505.01666 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:19:08.305689Z

measured 47 of 47 standing notices

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

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 362e8f9a-f6af-48db-9437-9724ae416b08 · outbound

This paper cites An introduction to structural health monitoring,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models An introduction to structural health monitoring,

Reference 1

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Observation 49d549e8-50bb-4ec3-8ef8-954a071bc453 · outbound

This paper cites Structural health monitoring techniques for aircraft composite structures,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Structural health monitoring techniques for aircraft composite structures,

Reference 2

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Observation 3d987909-8be7-4644-a92a-e7cea3661a99 · outbound

This paper cites State-of-the-art technologies for UAV inspections,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models State-of-the-art technologies for UAV inspections,

Reference 3

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Observation ddcb0ed5-4c77-4563-901d-49079341443d · outbound

This paper cites Life-cyclereliability-basedoptimizationofcivilandaerospace structures,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Life-cyclereliability-basedoptimizationofcivilandaerospace structures,

Reference 4

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Observation 8af35fdf-ca2a-46d1-9485-575ad0585797 · outbound

This paper cites Structural health monitoring: Closing the gap between research and industrial deployment,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Structural health monitoring: Closing the gap between research and industrial deployment,

Reference 5

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Observation a4cd2161-0729-47b2-87e8-1cf445bd034f · outbound

This paper cites Probabilistic active sensing acousto-ultrasound SHM based on non-parametric stochastic representations,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Probabilistic active sensing acousto-ultrasound SHM based on non-parametric stochastic representations,

Reference 6

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Observation 449004c1-1830-4c49-a27d-12057f2bda77 · outbound

This paper cites Towards Unified Probabilistic Rotorcraft Damage De- tection and Quantification via Non-parametric Time Series and Gaussian Process Regression Models,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Towards Unified Probabilistic Rotorcraft Damage De- tection and Quantification via Non-parametric Time Series and Gaussian Process Regression Models,

Reference 7

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Source-reported events for the cited work

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Observation 4384d622-601c-4093-af84-3a4a222086ba · outbound

This paper cites Damage detection sen- sitivity characterization of acousto-ultrasound-based structural health monitoring techniques,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Damage detection sen- sitivity characterization of acousto-ultrasound-based structural health monitoring techniques,

Reference 8

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Observation d32c6251-c4c4-4c69-aa4e-af94dcac7ed7 · outbound

This paper cites A probabilistic crack size quantification method using in-situ Lamb wave test and Bayesian updating,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models A probabilistic crack size quantification method using in-situ Lamb wave test and Bayesian updating,

Reference 9

Resolution
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Source-reported events for the cited work

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Observation fed4eb6f-c40b-4993-8754-083a5d08f804 · outbound

This paper cites A Lamb wave based fatigue crack length estimation method using finite element simulations,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models A Lamb wave based fatigue crack length estimation method using finite element simulations,

Reference 10

Resolution
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Source-reported events for the cited work

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Observation f29a5194-5937-4559-9596-a374271b517d · outbound

This paper cites Monitoring of fatigue crack propagation by damage index of ultrasonic guided waves calculated by various acoustic features,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Monitoring of fatigue crack propagation by damage index of ultrasonic guided waves calculated by various acoustic features,

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5e68475a-fc02-4ca7-9a50-9aae91f3a484 · outbound

This paper cites Active interface debonding detection of a concrete- filled steel tube with piezoelectric technologies using wavelet packet analysis,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Active interface debonding detection of a concrete- filled steel tube with piezoelectric technologies using wavelet packet analysis,

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9118afa5-f955-432b-b10f-626d93c5def0 · outbound

This paper cites Piezoelectric Wafer Active Sensors for Structural Health Monitoring of Com- posite Structures Using Tuned Guided Waves,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Piezoelectric Wafer Active Sensors for Structural Health Monitoring of Com- posite Structures Using Tuned Guided Waves,

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 01165a42-45e1-48ed-99c2-127cf5bea59e · outbound

This paper cites Multimodal structural health monitoring based on active and passive sensing,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multimodal structural health monitoring based on active and passive sensing,

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 225c4078-b41a-486f-bb90-1e011a81c563 · outbound

This paper cites Monitoring fatigue crack growth in narrow structural components using Lamb wave technique,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Monitoring fatigue crack growth in narrow structural components using Lamb wave technique,

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation eaca7266-108a-4c91-8ae2-a416ad17a2db · outbound

This paper cites Comparative study of deterioration of com- posite due to moisture using strain, electro-mechanical impedence, and guided waves,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Comparative study of deterioration of com- posite due to moisture using strain, electro-mechanical impedence, and guided waves,

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 40c37ffd-074e-47a5-8517-716fdf2214d2 · outbound

This paper cites In-situ acousto-ultrasonic monitoring of crack propagation in AL2024 alloy,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models In-situ acousto-ultrasonic monitoring of crack propagation in AL2024 alloy,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3731e688-bbeb-4ddb-8cde-326c2b1597de · outbound

This paper cites Uncertainty quantification of guided waves propagation for active sensing structural health monitoring,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Uncertainty quantification of guided waves propagation for active sensing structural health monitoring,

Reference 18

Resolution
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Source-reported events for the cited work

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Observation 11d7ebb3-d54a-4a69-b2bb-785d176c7df8 · outbound

This paper cites A stochastic global identification framework for aerospace structures operating under varying flight states,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models A stochastic global identification framework for aerospace structures operating under varying flight states,

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 74cef47a-da55-44ca-ae81-ad70951eae76 · outbound

This paper cites Support-vector networks,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Support-vector networks,

Reference 20

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Source-reported events for the cited work

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This paper cites an unresolved cited work.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Unresolved cited work

Reference 21

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Observation 1a84c966-d187-42bc-aead-e73f2d3411b2 · outbound

This paper cites Physics-constrained deep learn- ing for high-dimensional surrogate modeling and uncertainty quantification without labeled data,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Physics-constrained deep learn- ing for high-dimensional surrogate modeling and uncertainty quantification without labeled data,

Reference 22

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Source-reported events for the cited work

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Observation a6c83015-21ab-46aa-84bd-4fdf4b168e48 · outbound

This paper cites Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification,

Reference 23

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Source-reported events for the cited work

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Observation 94d3cd27-4f78-4791-b7fe-7dde9e1811f4 · outbound

This paper cites Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks

Reference 24

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Source-reported events for the cited work

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Observation f1eb07b6-e90f-4944-8153-1a4df9cdaad7 · outbound

This paper cites Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow,

Reference 25

Resolution
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Observation d4fe2f2d-6f19-422a-a33f-06bb021371a6 · outbound

This paper cites Numerical Gaussian processes for time- dependentandnonlinearpartialdifferentialequations,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Numerical Gaussian processes for time- dependentandnonlinearpartialdifferentialequations,

Reference 26

Resolution
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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This paper cites Uncertainty propagation using infinite mixture of gaus- sian processes and variational bayesian inference,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Uncertainty propagation using infinite mixture of gaus- sian processes and variational bayesian inference,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 84d32317-2f54-4054-8cb9-0c4736646f5c · outbound

This paper cites Multi-output separable Gaussian pro- cess: Towards an efficient, fully Bayesian paradigm for uncertainty quantification,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multi-output separable Gaussian pro- cess: Towards an efficient, fully Bayesian paradigm for uncertainty quantification,

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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This paper cites Gaussian processes in machine learning,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Gaussian processes in machine learning,

Reference 29

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation c74fde7c-0ef1-40a8-a2ee-90517f9c535a · outbound

This paper cites Statistical Time Series Meth- ods for Multicopter Fault Detection and Identification,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Statistical Time Series Meth- ods for Multicopter Fault Detection and Identification,

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 74655520-bb7d-4b1a-96ce-10461646954f · outbound

This paper cites Aircraft parametric structural load monitoring using gaussian process regression,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Aircraft parametric structural load monitoring using gaussian process regression,

Reference 31

Resolution
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raw_fallback, observed 2026-08-16T04:19:08.575643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e1df88d5-7417-4730-9ed2-db5e18f16177 · outbound

This paper cites Probabilistic Damage Quantificationvia the Integration of Non-parametric Time-series and Gaussian Process Regression Models,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Probabilistic Damage Quantificationvia the Integration of Non-parametric Time-series and Gaussian Process Regression Models,

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8854c62c-2e72-4d53-9509-5ee3e5f90588 · outbound

This paper cites An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.549679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.249232Z digest=sha256:11562b6ab8d20e4f05c3def6cb8293e2726544efd8a40d45c37665ee4e2da89f

Observation 0d2a5896-3387-47b0-9e03-bd764d8eca01 · outbound

This paper cites Multi-fidelity optimization via surrogate modelling,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multi-fidelity optimization via surrogate modelling,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.537052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.253738Z digest=sha256:029b51b3f2e01b9a691db4bd905bc6dd4d73bb46558d3f5093e69d3ca9b85b79

Observation 2b0f788c-1318-4c32-9562-dba6f2da1853 · outbound

This paper cites Recursive co-kriging model for design of computer experiments with multiple levels of fidelity,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Recursive co-kriging model for design of computer experiments with multiple levels of fidelity,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.524236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.258054Z digest=sha256:ff174ea96e490bd474388f4b465d36ec7a2c3b4b917ad96e76258497067761b1

Observation 03bb0b72-7ff8-4f0e-9feb-298a9e87ad99 · outbound

This paper cites Multi-fidelity modelling via recursive co-kriging and Gaussian–Markov random fields,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multi-fidelity modelling via recursive co-kriging and Gaussian–Markov random fields,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.510613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.262019Z digest=sha256:b2fcf8996bd36c325927b1ac406efac5ced2e3b4bd0d569afea794366b4a3835

Observation 1eef4a17-e78a-41ee-b29f-4a9ed77875a4 · outbound

This paper cites Com- bining experimental data and computer simulations, with an application to flyer plate experi- ments,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Com- bining experimental data and computer simulations, with an application to flyer plate experi- ments,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.497080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.265978Z digest=sha256:90c67a518cd5987692c7ca2b85e9d8d460fbde64ef254e6b4375c6f8ee83bbde

Observation d1f3a304-70ee-467f-ae8f-6a3075e7b95f · outbound

This paper cites Computer model calibration using high-dimensional output,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Computer model calibration using high-dimensional output,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.483492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.269812Z digest=sha256:046a45e564485d502b66ce5e056c7e4a1c4ca92f8bd7739a71db7ce52d836753

Observation 672622bf-7613-4d68-9185-3b561e6a48d9 · outbound

This paper cites Deep Multi-fidelity Gaussian Processes.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Deep Multi-fidelity Gaussian Processes

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T04:19:08.273621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:19:08.273621Z digest=sha256:e1152bdff45b4ae1f09cd8404c06229854cade5712e4c6aed68159472c9e7797

Observation 8a2e4787-7fc6-4f11-8b29-5ae78f63bbd9 · outbound

This paper cites Inferring solutions of differential equations using noisy multi-fidelity data,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Inferring solutions of differential equations using noisy multi-fidelity data,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.470403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.278079Z digest=sha256:5b53a5b1c1319b5965022ad4769065c7cea92343b7936e180e5c624607bc7f80

Observation 7f5f229a-523b-473e-8b22-b1e0b30eb6a8 · outbound

This paper cites Machine learning of linear differential equa- tionsusingGaussianprocesses,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Machine learning of linear differential equa- tionsusingGaussianprocesses,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.458089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.282159Z digest=sha256:9574ffd1f916d3c4cee93b926f1a3cb3ba62c0b535d0d170a4d06ebfa51ed726

Observation fd161133-7a15-4b5e-be30-d01b4f0e51cf · outbound

This paper cites Multi-fidelity Bayesian neural networks: Al- gorithms and applications,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multi-fidelity Bayesian neural networks: Al- gorithms and applications,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.443928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.285881Z digest=sha256:a33128be12f11d2b983e694be31f3f73f33d388d1cfe3ccb3371e9ab17277264

Observation 8098d8cd-3831-4240-9a6c-e16658b7fbd2 · outbound

This paper cites A deep neural network, multi-fidelity surrogate model approach for Bayesian model updating in shm,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models A deep neural network, multi-fidelity surrogate model approach for Bayesian model updating in shm,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.430524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.290124Z digest=sha256:da991af3a1b2f3f9c371ddea4121ae545241575652a0f01baa327953df226d79

Observation 28bed2c3-7481-471b-a5aa-3033f5edde6e · outbound

This paper cites Damage State Estimation via Multi-fidelity Gaussian Process Regression Models for Active-Sensing Structure Health Monitoring,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Damage State Estimation via Multi-fidelity Gaussian Process Regression Models for Active-Sensing Structure Health Monitoring,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.417447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.294149Z digest=sha256:c62e410c262b4ca8e83062b531a8683d57990c66dc3ff11b5916ee20eb393a5e

Observation feb6427d-ad4c-46b4-90f4-a0d9c092c28c · outbound

This paper cites Loadmonitoringandcompensationstrategiesforguided- waves based structural health monitoring using piezoelectric transducers,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Loadmonitoringandcompensationstrategiesforguided- waves based structural health monitoring using piezoelectric transducers,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.403616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.297937Z digest=sha256:0c36d26f27b5f238027c020326b1972028314dc9550d3de0bde42e58d4e21fa2

Observation 53dc3ff0-1843-46e7-93ff-9b74702b3eb5 · outbound

This paper cites A novel physics-based temperature compensation model for structural health monitoring using ultrasonic guided waves,.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models A novel physics-based temperature compensation model for structural health monitoring using ultrasonic guided waves,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:19:08.389450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.301787Z digest=sha256:87007ef1d9da759437630084cee259e3fbf9cd0c8641781303f729beface428e

Observation 2acccf01-bb4d-4cfe-b793-cdd225147489 · outbound

This paper cites Gaussian Process Regression for Active Sensing Probabilistic Structural Health Monitoring: Experimental Assessment Across Multiple Damage and Loading Scenarios.

Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Gaussian Process Regression for Active Sensing Probabilistic Structural Health Monitoring: Experimental Assessment Across Multiple Damage and Loading Scenarios

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-16T04:19:08.347640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T04:19:08.305689Z digest=sha256:778196e917c8a4def2b601b09dc1e7d00c381e0605ef14535edb9d4ac6b0c22d

Pith citing papers

No inbound Pith citation observations are available.