Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:19:08.305689Z
Paper Citation Record · LEDGER
As of 16 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:19:08.305689Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
47 of 47 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 362e8f9a-f6af-48db-9437-9724ae416b08 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models An introduction to structural health monitoring,
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 49d549e8-50bb-4ec3-8ef8-954a071bc453 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Structural health monitoring techniques for aircraft composite structures,
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3d987909-8be7-4644-a92a-e7cea3661a99 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models State-of-the-art technologies for UAV inspections,
Reference 3
Source-reported events for the cited work
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Observation ddcb0ed5-4c77-4563-901d-49079341443d · outbound
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
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Structural health monitoring: Closing the gap between research and industrial deployment,
Reference 5
Source-reported events for the cited work
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Observation a4cd2161-0729-47b2-87e8-1cf445bd034f · outbound
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
Source-reported events for the cited work
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Observation 449004c1-1830-4c49-a27d-12057f2bda77 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4384d622-601c-4093-af84-3a4a222086ba · outbound
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
Source-reported events for the cited work
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Observation d32c6251-c4c4-4c69-aa4e-af94dcac7ed7 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fed4eb6f-c40b-4993-8754-083a5d08f804 · outbound
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
Source-reported events for the cited work
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Observation f29a5194-5937-4559-9596-a374271b517d · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5e68475a-fc02-4ca7-9a50-9aae91f3a484 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9118afa5-f955-432b-b10f-626d93c5def0 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 01165a42-45e1-48ed-99c2-127cf5bea59e · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multimodal structural health monitoring based on active and passive sensing,
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 225c4078-b41a-486f-bb90-1e011a81c563 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation eaca7266-108a-4c91-8ae2-a416ad17a2db · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 40c37ffd-074e-47a5-8517-716fdf2214d2 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models In-situ acousto-ultrasonic monitoring of crack propagation in AL2024 alloy,
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3731e688-bbeb-4ddb-8cde-326c2b1597de · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 11d7ebb3-d54a-4a69-b2bb-785d176c7df8 · outbound
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
Source-reported events for the cited work
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Observation 74cef47a-da55-44ca-ae81-ad70951eae76 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Support-vector networks,
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bfa388a7-2f71-4bef-b5f1-046a3ccb7c9c · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Unresolved cited work
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1a84c966-d187-42bc-aead-e73f2d3411b2 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a6c83015-21ab-46aa-84bd-4fdf4b168e48 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 94d3cd27-4f78-4791-b7fe-7dde9e1811f4 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1eb07b6-e90f-4944-8153-1a4df9cdaad7 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d4fe2f2d-6f19-422a-a33f-06bb021371a6 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Numerical Gaussian processes for time- dependentandnonlinearpartialdifferentialequations,
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 10eed45d-7bb6-4ff4-9393-34dd0c53bf89 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 84d32317-2f54-4054-8cb9-0c4736646f5c · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9d333206-f64c-43d0-8084-31e8128dee32 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Gaussian processes in machine learning,
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c74fde7c-0ef1-40a8-a2ee-90517f9c535a · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Statistical Time Series Meth- ods for Multicopter Fault Detection and Identification,
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 74655520-bb7d-4b1a-96ce-10461646954f · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Aircraft parametric structural load monitoring using gaussian process regression,
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e1df88d5-7417-4730-9ed2-db5e18f16177 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8854c62c-2e72-4d53-9509-5ee3e5f90588 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0d2a5896-3387-47b0-9e03-bd764d8eca01 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multi-fidelity optimization via surrogate modelling,
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2b0f788c-1318-4c32-9562-dba6f2da1853 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 03bb0b72-7ff8-4f0e-9feb-298a9e87ad99 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1eef4a17-e78a-41ee-b29f-4a9ed77875a4 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d1f3a304-70ee-467f-ae8f-6a3075e7b95f · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Computer model calibration using high-dimensional output,
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 672622bf-7613-4d68-9185-3b561e6a48d9 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Deep Multi-fidelity Gaussian Processes
Reference 39
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a2e4787-7fc6-4f11-8b29-5ae78f63bbd9 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Inferring solutions of differential equations using noisy multi-fidelity data,
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7f5f229a-523b-473e-8b22-b1e0b30eb6a8 · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Machine learning of linear differential equa- tionsusingGaussianprocesses,
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fd161133-7a15-4b5e-be30-d01b4f0e51cf · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Multi-fidelity Bayesian neural networks: Al- gorithms and applications,
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8098d8cd-3831-4240-9a6c-e16658b7fbd2 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 28bed2c3-7481-471b-a5aa-3033f5edde6e · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation feb6427d-ad4c-46b4-90f4-a0d9c092c28c · outbound
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models Loadmonitoringandcompensationstrategiesforguided- waves based structural health monitoring using piezoelectric transducers,
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 53dc3ff0-1843-46e7-93ff-9b74702b3eb5 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2acccf01-bb4d-4cfe-b793-cdd225147489 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
No inbound Pith citation observations are available.