Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T00:50:09.088693Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.26038.
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 2026-08-01T00:50:09.088693Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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
35 of 35 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 31795f05-b5b3-4782-843b-82278e4d062e · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Machinery health prognostics: A systematic review from data acquisition to rul prediction,
Reference 1
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Observation 85407ae5-dda3-4f83-87da-c355759a831a · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Prognostics and health management (phm): Where are we and where do we (need to) go in theory and practice,
Reference 2
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Observation 8df3782a-4b06-4aac-bff8-6cedd653f8df · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Recent advances and trends of predictive maintenance from data-driven machine prog- nostics perspective,
Reference 3
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Observation 0e6b5df4-ec5b-426b-8dcb-6f6f1ae836c5 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling A Survey of Predictive Maintenance: Systems, Purposes and Approaches
Reference 4
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Observation 4f7b28f0-5042-4051-aec7-27a5d4d68d5b · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Degradation modeling and rul prediction using wiener process subject to multiple change points and unit heterogeneity,
Reference 5
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Observation c6c26079-b5fa-41ef-bdd1-38795936e404 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Condition-based maintenance planning for systems subject to dependent soft and hard failures,
Reference 6
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Observation 07ce6d4e-8804-42bb-bb05-3e79d3f2b89b · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Remaining useful life prediction of individual units subject to hard failure,
Reference 7
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Observation dfa365ac-c9c2-4c40-aa9e-298d361cc86e · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Functional principal components analysis on moving time windows of longitudinal data: dynamic prediction of times to event,
Reference 8
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Observation c38ffd62-58b4-40db-8468-dede03f011dd · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Joint models for event prediction from time series and survival data,
Reference 9
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Observation 1118d31b-2e1a-4a59-a234-8848e31cea3c · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling A neural-network-based propor- tional hazard model for iot signal fusion and failure prediction,
Reference 10
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Observation 61b1de79-f55f-4eea-afbe-77d338d4597f · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Joint modeling of degradation signals and time-to-event data for the pre- diction of remaining useful life,
Reference 11
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Observation dbcda38b-f654-4e72-b3c9-a3beec8368e0 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Deepsurv: personalized treatment recommender system using a cox proportional hazards deep neural network,
Reference 12
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Observation 7b0d9d51-5c00-40a7-b65f-e97fe29b1469 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Deephit: A deep learning approach to survival analysis with competing risks,
Reference 13
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Observation 9735d93d-c2d4-4f42-8fc0-cd8fb12777fe · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Deep convolutional neural network based regression approach for estimation of remaining useful life,
Reference 14
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Unavailable: canonical work link unavailable.
Observation bfa6a575-7fb5-4e1b-bfd0-131e58a89c07 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Remaining useful life estimation in prognostics using deep convolution neural networks,
Reference 15
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Observation 4b53a414-6358-425b-a5b1-77271f400fb4 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Dual aspect self-attention based on transformer for remaining useful life prediction,
Reference 16
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Observation da3dadf4-e771-4483-a7e7-2c9ea2856224 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Privacy- preserving and sensor-fused framework for prognostic & health man- agement in leased manufacturing system,
Reference 17
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Observation c8ff2e53-4d5f-414a-9457-e83b3d55b1e0 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Communication-efficient learning of deep networks from decentralized data,
Reference 18
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Observation 3939d9a0-463f-47dd-ab9c-6e3c03bc40ef · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Advances and open problems in federated learning,
Reference 19
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Observation ae9eb796-2adf-4783-b136-92432d4ce906 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Federated optimization in heterogeneous networks,
Reference 20
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Observation 12fee7f1-5000-47a1-adf7-1c114fd0878d · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Scaffold: Stochastic controlled averaging for federated learning,
Reference 21
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Observation eaf9a122-bda0-4612-be76-6042a9a383fa · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Empirical Convergence Analysis of Federated Averaging for Failure Prognosis *,
Reference 22
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Observation e2b3f0a7-df50-443d-a27c-ef1d75baa72c · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling A Federated Learning-based Industrial Health Prognostics for Heterogeneous Edge Devices using Matched Feature Extraction
Reference 23
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Observation 99241e9f-ae2e-4298-beaa-02d7affd12ad · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Partial likelihood,
Reference 24
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Observation 773fadcb-3cd9-42e3-812b-91aa72a9aab5 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Federated Survival Analysis with Discrete-Time Cox Models
Reference 25
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Observation 45fcc247-cde8-4df0-8005-738d3cdbfd38 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling A federated cox model with non-proportional hazards,
Reference 26
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Observation dd284ce7-2ccd-42d4-b4e2-4792b0241603 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Cox’s regression model for counting processes: a large sample study,
Reference 27
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Unavailable: canonical work link unavailable.
Observation 6d8acbdf-a394-45e3-85cb-d076d4f6cb73 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Regression analysis of grouped survival data with application to breast cancer data,
Reference 28
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Observation 59063ef8-dc94-4106-9b19-2f733fc09f3d · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Unresolved cited work
Reference 29
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Observation 13194f79-96f8-4870-af29-7fd0d6f29367 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Discrete-time methods for the analysis of event histories,
Reference 30
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Observation 49a0505a-fd4a-4446-b5c7-3d9cccb40818 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling A practical guide to understanding kaplan-meier curves,
Reference 31
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Observation df25b2d0-dbfb-4614-8db5-360c3f26c933 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Degradation modeling and monitoring of truncated degradation signals,
Reference 32
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Observation 70fa7eae-59d9-4020-af0a-e377791dfc26 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Neural Machine Translation by Jointly Learning to Align and Translate
Reference 33
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Observation 92fc6cea-54cc-4b38-aa31-01372d8db1d4 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling Performance benchmarking and analysis of prognostic methods for cmapss datasets
Reference 34
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Observation f9738a67-c4d8-4367-a508-d98b9316f118 · outbound
Collaborative System Failure Prognostics via Federated Longitudinal-Survival Modeling A similarity-based prognostics approach for remaining useful life estimation of engineered systems,
Reference 35
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No inbound Pith citation observations are available.