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Paper Citation Record · LEDGER

Multiple data-driven missing imputation

As of 19 August 2026, this Paper Citation Record lists 95 of 95 outbound references and 1 inbound Pith citation observation for arXiv:2507.03061.

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

pith.paper-citation-record.v1
2507.03061 v1

Coverage vector

measured 95 of 95 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:27:37.191263Z

measured 96 of 96 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:39:09.549449Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T12:39:13.420212Z

Reference resolution

95 of 95 outbound references displayed

  • verified exact28
  • verified fuzzy21
  • unresolved31
  • parse uncertain0
  • malformed identifier5
  • metadata mismatch10

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f412bb30-f8cd-418c-af02-7e77c8a5a3bd · outbound

This paper cites Missing data are common in real-world datasets, and time series data are especially susceptible.

Multiple data-driven missing imputation Missing data are common in real-world datasets, and time series data are especially susceptible

Reference 1

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Unavailable: canonical work link unavailable.

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Observation cb80e451-6aef-4004-b624-459b4e40991f · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 2

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Observation 7e65b2f8-ed7f-4014-a8ad-9e69a2afa489 · outbound

This paper cites imputation of missing data.

Multiple data-driven missing imputation imputation of missing data

Reference 3

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Observation af44dcf8-95c9-4a6a-9a4e-6876031474cf · outbound

This paper cites This section details the datasets used, the imputation methods chosen for comparison, and the metrics employed for performance assessment.

Multiple data-driven missing imputation This section details the datasets used, the imputation methods chosen for comparison, and the metrics employed for performance assessment

Reference 4

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Observation 3b055ae3-000c-40ac-91f0-9737a9ea5560 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 5

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Unavailable: canonical work link unavailable.

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Observation baee386f-4730-43ef-98d5-2d474ad32932 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 6

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Observation 193ca5e4-889c-4a80-8003-7e07f5ccf0aa · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 7

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Observation 0c1dde22-86c7-4a37-b1b6-52597a2ab21f · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 8

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Observation 43398e86-f67c-4436-b85e-dc469a3ee864 · outbound

This paper cites KZImputer.

Multiple data-driven missing imputation KZImputer

Reference 9

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Observation ab19366f-2f66-45a6-a52a-37d471be9834 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 10

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Observation 54e275d7-64f2-4162-8ecf-36507c2f33d5 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 11

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Observation 0da5e2fc-d7c2-47a6-9d9d-a2d6d288c0ff · outbound

This paper cites (Note: KZImputer uses this for mid-gaps, so this comparison will be particularly relevant for start/end gaps and overall performance).

Multiple data-driven missing imputation (Note: KZImputer uses this for mid-gaps, so this comparison will be particularly relevant for start/end gaps and overall performance)

Reference 12

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Observation 0ffcd2bd-b4d9-42bd-a2dd-f99a67a627a0 · outbound

This paper cites Suitable for time series or sequential data.

Multiple data-driven missing imputation Suitable for time series or sequential data

Reference 13

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Observation 4d3fb11b-3863-478b-8e51-101406ed9065 · outbound

This paper cites Often used when future values are assumed to influence missing entries.

Multiple data-driven missing imputation Often used when future values are assumed to influence missing entries

Reference 14

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Observation 1f668cbd-6d8e-490d-92c1-ecedb9d18aa0 · outbound

This paper cites Captures non-linear trends better than linear interpolation.

Multiple data-driven missing imputation Captures non-linear trends better than linear interpolation

Reference 15

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Observation 0e8ce23f-1333-4639-913d-85a9a80e0eff · outbound

This paper cites Effective for capturing local patterns in the data.

Multiple data-driven missing imputation Effective for capturing local patterns in the data

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 98ed7607-23a0-46e8-afc1-b307035361cb · outbound

This paper cites Useful for multivariate data imputation.

Multiple data-driven missing imputation Useful for multivariate data imputation

Reference 17

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 37e0a3cd-2147-4d22-96e4-ff1dfa9dda20 · outbound

This paper cites Less sensitive to outliers compared to RMSE.

Multiple data-driven missing imputation Less sensitive to outliers compared to RMSE

Reference 18

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f9a5d5fe-c701-4104-8eb7-89cc12faceb9 · outbound

This paper cites More sensitive to outliers than MAE.

Multiple data-driven missing imputation More sensitive to outliers than MAE

Reference 19

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 323ebc6a-9e44-4d0e-b072-fe256d344d6f · outbound

This paper cites Undefined when actual values are zero.

Multiple data-driven missing imputation Undefined when actual values are zero

Reference 20

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6cd5ae2b-8acc-45da-8491-9f6ce0859bc4 · outbound

This paper cites Typically expressed as percentage for interpretability.

Multiple data-driven missing imputation Typically expressed as percentage for interpretability

Reference 21

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0980d67d-c024-4686-9528-1bf675275d61 · outbound

This paper cites Higher values indicate better model fit to data.

Multiple data-driven missing imputation Higher values indicate better model fit to data

Reference 22

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Observation 699db5cf-9f3b-4a9c-89a9-2510bb0946a9 · outbound

This paper cites Square root of JS divergence forms a proper distance metric.

Multiple data-driven missing imputation Square root of JS divergence forms a proper distance metric

Reference 23

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Observation b63e88f7-dce7-4da4-b091-408af9ac0692 · outbound

This paper cites Particularly useful for comparing distributions with different supports.

Multiple data-driven missing imputation Particularly useful for comparing distributions with different supports

Reference 24

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Observation 4b71da69-7c98-4a62-88d5-ee982ae891ca · outbound

This paper cites Values closer to zero indicate better preservation of correlational structure.

Multiple data-driven missing imputation Values closer to zero indicate better preservation of correlational structure

Reference 25

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Observation 9093dfd6-2771-4f15-abd7-95aea3cc8cbd · outbound

This paper cites Gap’s number.

Multiple data-driven missing imputation Gap’s number

Reference 26

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f53173fc-f98e-43a2-bd54-5853a73e6fea · outbound

This paper cites Key observations are summarized in Tables 2 and 3.

Multiple data-driven missing imputation Key observations are summarized in Tables 2 and 3

Reference 27

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ec654ab3-038c-4fc3-baa0-6eba87a9722d · outbound

This paper cites Suitable for domains with degraded sensors or telemetry data (e.g., remote sensing, anomaly-prone IoT).

Multiple data-driven missing imputation Suitable for domains with degraded sensors or telemetry data (e.g., remote sensing, anomaly-prone IoT)

Reference 28

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Observation 1f9771fe-58f0-4e28-9da2-43fd1933c86f · outbound

This paper cites Ensures dynamic consistency essential for downstream tasks (e.g., forecasting, root cause analysis).

Multiple data-driven missing imputation Ensures dynamic consistency essential for downstream tasks (e.g., forecasting, root cause analysis)

Reference 29

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1e66fb27-d5a7-4d32-bc5d-df3ae611d28c · outbound

This paper cites Optimal for environmental, behavioral, or energy datasets where structural evolution is prominent.

Multiple data-driven missing imputation Optimal for environmental, behavioral, or energy datasets where structural evolution is prominent

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 79719def-6be8-40ae-9201-f98eeadecc09 · outbound

This paper cites Enables valid application of classical models (e.g., ARIMA, Kalman Filters) that assume stationarity.

Multiple data-driven missing imputation Enables valid application of classical models (e.g., ARIMA, Kalman Filters) that assume stationarity

Reference 31

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c0ce3584-107b-462d-bf2d-480de0307f7b · outbound

This paper cites Use simpler methods (e.g., spline, EMA) in low-sparsity unless structural fidelity is mission-critical.

Multiple data-driven missing imputation Use simpler methods (e.g., spline, EMA) in low-sparsity unless structural fidelity is mission-critical

Reference 32

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Observation 1f8cd8a9-4d7e-4dc1-8563-e4a6c8208194 · outbound

This paper cites Enhances quality and stability of learning pipelines via structured, nonparametric imputation groundwork.

Multiple data-driven missing imputation Enhances quality and stability of learning pipelines via structured, nonparametric imputation groundwork

Reference 33

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c90571d1-1e71-4903-9fd3-0b084ce19454 · outbound

This paper cites The methodology, imple mented in Python, combines localized averaging with interpolation to balance accuracy, computational efficiency, and ease of use.

Multiple data-driven missing imputation The methodology, imple mented in Python, combines localized averaging with interpolation to balance accuracy, computational efficiency, and ease of use

Reference 34

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d5436bc9-de7f-4554-9afc-c13b0a2b8c37 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 35

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 406be64e-80e3-45bb-9846-e4360c59562e · outbound

This paper cites (2021), Kalman filter algorithm versus other methods of estimating missing values: time series evidence.

Multiple data-driven missing imputation (2021), Kalman filter algorithm versus other methods of estimating missing values: time series evidence

Reference 36

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4adba0f1-8217-47f4-acf0-f38b0de9249e · outbound

This paper cites and Miskon, S.

Multiple data-driven missing imputation and Miskon, S

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d6fc7a4e-017c-4aa0-a25e-e093217433a5 · outbound

This paper cites Conceptual framework as a guide to choose appropriate imputation method for missing values in a clinical structured dataset.

Multiple data-driven missing imputation Conceptual framework as a guide to choose appropriate imputation method for missing values in a clinical structured dataset

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5a94d532-548b-4b34-9cc2-9ce53e130a0c · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 39

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T20:27:37.008491Z digest=sha256:f6db20066813cf620c8ef9588f417e574a933214021df3a8e588d4ad10f9bb37

Observation a5e35af7-2e06-4e1e-8b34-f1818615f0e8 · outbound

This paper cites and Pinto, F.C.

Multiple data-driven missing imputation and Pinto, F.C

Reference 40

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation bd792992-0053-4337-9fa8-7f0a0ff14284 · outbound

This paper cites G., & Bland, J.

Multiple data-driven missing imputation G., & Bland, J

Reference 41

Resolution
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raw_fallback, observed 2026-08-06T20:27:39.077071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 329e47f7-4607-484d-801d-da70b5f802a1 · outbound

This paper cites and Gad, I.

Multiple data-driven missing imputation and Gad, I

Reference 42

Resolution
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raw_fallback, observed 2026-08-06T20:27:39.004874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9bf380fd-6905-419d-8237-e927d8c4b13b · outbound

This paper cites A Review of Hot Deck Imputation for Survey Non -response.

Multiple data-driven missing imputation A Review of Hot Deck Imputation for Survey Non -response

Reference 43

Resolution
verified exact
raw_fallback, observed 2026-08-06T20:27:38.938323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 84ffd37b-8311-4015-ae92-57aa50dc22d0 · outbound

This paper cites J., Stuart, E.

Multiple data-driven missing imputation J., Stuart, E

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.030013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.030013Z digest=sha256:3e11f0fc4abb8583127ccc7383d117b8922a62eef92d9d4971653fc877d18418

Observation 52f6e521-6e27-441b-98c3-ce6e1088a133 · outbound

This paper cites W., & Hatch, L.

Multiple data-driven missing imputation W., & Hatch, L

Reference 47

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:38.855424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d7a5affe-ac3c-4b6c-9777-7aa760c368db · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:27:39.142549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 10a460f3-2713-43aa-8741-68994e48c552 · outbound

This paper cites BRITS: Bidirectional Recurrent Imputation for Time Series.

Multiple data-driven missing imputation BRITS: Bidirectional Recurrent Imputation for Time Series

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.038412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.038412Z digest=sha256:2541f6665a448d1d91b0f8fc36f54193730a9892ad21c0a724dcd238f8207852

Observation f6ac1c32-4551-48d7-b702-7eaffa7faf18 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 50

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:38.764987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 03e81954-ae27-4956-aa51-5416af2b4550 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 51

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.467380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e59e5686-43a5-4f84-8691-f9edc2fd62fb · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 52

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.457558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8f9626e0-281d-4533-8aeb-fd8421e58ba9 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 53

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.448176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4c52208b-de6f-4e4e-a935-0cefa460e0f8 · outbound

This paper cites (2023) Comparison of Imputation Methods for Univariate Time Series.

Multiple data-driven missing imputation (2023) Comparison of Imputation Methods for Univariate Time Series

Reference 54

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.437472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.054718Z digest=sha256:ca5e47566e3560c96be384b04c4bce747413e890bb730a99f6f5892767f5d0e6

Observation 0f5f5b32-35a8-47a8-8e3a-9f423c74c834 · outbound

This paper cites and Tabona, O.

Multiple data-driven missing imputation and Tabona, O

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.057953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.057953Z digest=sha256:69bdae6909a5ce019663bd51b425fbde61e5c54841f6dcdf91b2d992a94c1e6a

Observation f1f97d35-5eb6-4ebb-8044-e3ddd853fd3e · outbound

This paper cites (2022) Applied Missing Data Analysis.

Multiple data-driven missing imputation (2022) Applied Missing Data Analysis

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:27:39.133114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.061128Z digest=sha256:d8f52b158e239f80548b71d532f6ff1c58a07e9060ec795cad5ac28558310566

Observation 270d363b-da4d-4ed4-832f-62e22838f63e · outbound

This paper cites EMHIRES dataset.

Multiple data-driven missing imputation EMHIRES dataset

Reference 57

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.419772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c5be6555-a3cc-4f4a-a3c4-68c193bae130 · outbound

This paper cites Accuracy of random -forest-based imputation of missing data in the presence of non - normality, non-linearity, and interaction.

Multiple data-driven missing imputation Accuracy of random -forest-based imputation of missing data in the presence of non - normality, non-linearity, and interaction

Reference 59

Resolution
malformed identifier
doi_truncated, observed 2026-08-06T20:27:37.409699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.070333Z digest=sha256:84d8a7770e21b835a50da3e91e608843aad94de27bb78d6b1148a27ffa743918

Observation 0fe331cd-3617-4865-a653-db3c15f2ec7f · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 60

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.399753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation febc5dff-f857-4935-aedd-169d6218251c · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 61

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:38.613408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation bd307bc8-260a-46d2-9198-58d994236882 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 62

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.079101Z digest=sha256:13ff106c55ab9321889c29e0c398b4d0ac143611edb830fedfac44f6c06befe9

Observation 71ea4f19-7b12-4f6f-a6ad-efaf8f9bb125 · outbound

This paper cites Conceptual fundamentals of a theory of mathematical interpretation.

Multiple data-driven missing imputation Conceptual fundamentals of a theory of mathematical interpretation

Reference 63

Resolution
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raw_fallback, observed 2026-08-06T20:27:38.461941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation af6afbf2-d9b2-46ab-a919-a560163731ce · outbound

This paper cites (2021) Addressing Missing Data in Educational Evaluation: Predictive Mean Matching Imputation for Test Score Data.

Multiple data-driven missing imputation (2021) Addressing Missing Data in Educational Evaluation: Predictive Mean Matching Imputation for Test Score Data

Reference 64

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.390117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 35dc50b5-fc3e-44c7-8091-557971616f0a · outbound

This paper cites Exponential moving average versus moving exponential average.

Multiple data-driven missing imputation Exponential moving average versus moving exponential average

Reference 65

Resolution
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doi, observed 2026-08-06T20:27:37.379886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 32b1fe91-7533-45b1-9555-57bb373b2138 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 66

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.369506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ff7d31f3-10b2-4954-93d7-4dbf2c9df290 · outbound

This paper cites and Samad, M.D.

Multiple data-driven missing imputation and Samad, M.D

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.094272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.094272Z digest=sha256:59a87beadd87bc57ba5dacc1c34a9647fff356eecc6ae6865bdd6c829cb0615d

Observation d8f81dc3-3b12-4ace-9bd3-0115a7d99884 · outbound

This paper cites H., Park, Y.

Multiple data-driven missing imputation H., Park, Y

Reference 68

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:38.325667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e0d599b8-ff82-4579-bf28-7887cf18db97 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.101077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.101077Z digest=sha256:cc6be2081bee61f1e73ed2c708b34c9d7189fa3f9ba9ad5b7a5ee33c7ac1d00e

Observation fbfd5720-4bd4-439c-9b62-5da05ab579df · outbound

This paper cites A statistical learning framework for the intelligent imputation of offshore wind farm missing SCADA data.

Multiple data-driven missing imputation A statistical learning framework for the intelligent imputation of offshore wind farm missing SCADA data

Reference 70

Resolution
verified exact
raw_fallback, observed 2026-08-06T20:27:38.250316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1096d638-9b81-4740-b17f-40f66fb33164 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 71

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.353407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d5804b74-d2c5-457a-bbc7-cb36ee392c30 · outbound

This paper cites C.P.; Jiang, F.; Chen, W.; Wang, M.; Zhai.

Multiple data-driven missing imputation C.P.; Jiang, F.; Chen, W.; Wang, M.; Zhai

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.109962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.109962Z digest=sha256:6209fbc4470a5453ffac26c768f00c1eef83cde83e747ef7e7e211391376686b

Observation 96be179d-4a78-4b6d-ab57-82ce152b3810 · outbound

This paper cites and Akbar, M.I.

Multiple data-driven missing imputation and Akbar, M.I

Reference 73

Resolution
verified exact
raw_fallback, observed 2026-08-06T20:27:38.100652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.113062Z digest=sha256:58ae22df35c6ecec03f82f7986baab39f45f5a483ff7c08c6308f01a11b2dba9

Observation 9b794435-4482-4165-998e-a95f3c9379ba · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 74

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.343676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.116142Z digest=sha256:46a226d4625c7a80f02da50e4ff473980eb4a380d7d5475bdabaf14d8fc1beb3

Observation 09e289b1-5b5f-43a4-a146-5304eb3307ed · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 75

Resolution
verified exact
doi, observed 2026-08-06T20:27:37.334088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.119442Z digest=sha256:c85baf0e43a14dfde2c65fd875284575e09b2f9b462ff9501491dc14365c4c01

Observation d6ea3d6f-502b-4fe5-a31f-153835b40ccb · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.122787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.122787Z digest=sha256:ab487c524cbba69d6ba0ad9a41c7f6cf392dd2b03ac9da084521342c70f65d4a

Observation 0e9ff91d-7b78-42da-ad87-00073d37280b · outbound

This paper cites , Mikheev, I.

Multiple data-driven missing imputation , Mikheev, I

Reference 77

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:38.008664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.125943Z digest=sha256:2a8b2a44bf9c5dd9d7af717bf1e8ba182f35d4c35f8fe3d5059ad4cc24370f0b

Observation d9e38fd4-db06-4da9-8f0a-ffd167649bb5 · outbound

This paper cites and Askounis, D.

Multiple data-driven missing imputation and Askounis, D

Reference 78

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:37.879875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.129289Z digest=sha256:136472a305766e3878fafea68b4012e222f27eefc782a875c18c34390f1bf2b8

Observation deffc757-7c55-479d-bf25-7083429af02f · outbound

This paper cites A novel wind turbine data imputation method with multiple optimizations based on GANs.

Multiple data-driven missing imputation A novel wind turbine data imputation method with multiple optimizations based on GANs

Reference 79

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T20:27:37.816123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T20:27:37.132223Z digest=sha256:6273a0f07c3c19c6eebb12e1727c0c189f82908f2193e168e3b32da28d8fa9d7

Observation 154af5c0-4027-4421-9f93-59d4e0356081 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-06T20:27:37.135481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:27:37.135481Z digest=sha256:776efca322b57bada5d002a9b9e88387d2c2476fa18682fa7c6b5a3aeaa7d77f

Observation f79e7484-3d16-41ad-8cdd-57aab702b1f8 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 81

Resolution
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Observation 5ff92226-db45-46a8-aa2d-18a1a301a7ef · outbound

This paper cites Simulation of exchange processes in multi-component environments with account of data uncertainty.

Multiple data-driven missing imputation Simulation of exchange processes in multi-component environments with account of data uncertainty

Reference 82

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2f2796aa-65a3-4d1c-9e4d-dc0c4e78baa0 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 83

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 62533e28-4cea-4cdf-b1d9-3660a5ae70a1 · outbound

This paper cites and Trubitsyna, I.

Multiple data-driven missing imputation and Trubitsyna, I

Reference 84

Resolution
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Observation ef7695fd-f4e6-4f47-845a-abfc4d57f5de · outbound

This paper cites Blomberg, Orlin S.

Multiple data-driven missing imputation Blomberg, Orlin S

Reference 85

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 86

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fde6813b-a6ae-48bf-898e-b06226a4fe30 · outbound

This paper cites (2024) Applications: Imputation of Missing Hydrometeorological Data.

Multiple data-driven missing imputation (2024) Applications: Imputation of Missing Hydrometeorological Data

Reference 87

Resolution
verified exact
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Observation f48477c3-70f8-482b-9d85-238ce51bbc14 · outbound

This paper cites and Singh, D.P.

Multiple data-driven missing imputation and Singh, D.P

Reference 88

Resolution
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Observation b498cd67-1697-478b-a4c3-9577af2f449f · outbound

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Multiple data-driven missing imputation Unresolved cited work

Reference 90

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f4bd96c7-d159-4d61-b4ca-60c04d1b5329 · outbound

This paper cites an unresolved cited work.

Multiple data-driven missing imputation Unresolved cited work

Reference 91

Resolution
unresolved
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Observation 280007cc-da3d-447f-9d44-0d3a1c17d156 · outbound

This paper cites 2018 Scada Data of a Wind Turbine in Turkey.

Multiple data-driven missing imputation 2018 Scada Data of a Wind Turbine in Turkey

Reference 92

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 910a0c93-b70d-4ff0-958f-6219a5daadcf · outbound

This paper cites E., Halvorson, M., King, K.

Multiple data-driven missing imputation E., Halvorson, M., King, K

Reference 93

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dd08e48c-c928-486d-b9d4-cee90e1b6437 · outbound

This paper cites A Graph-Based Approach for Missing Sensor Data Imputation,.

Multiple data-driven missing imputation A Graph-Based Approach for Missing Sensor Data Imputation,

Reference 94

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4ed49f89-e98f-4baa-8edc-1140499f2562 · outbound

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Multiple data-driven missing imputation Unresolved cited work

Reference 95

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cb262589-efde-493d-b836-0a17fdecc6f0 · outbound

This paper cites Complex systems modeling with intelligent control elements.

Multiple data-driven missing imputation Complex systems modeling with intelligent control elements

Reference 96

Resolution
verified exact
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Observation c1a1beb2-fe38-42c8-baf2-e156072db6d1 · outbound

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Multiple data-driven missing imputation Unresolved cited work

Reference 97

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4006d520-0875-4bdf-837e-f88d12ba1293 · outbound

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Multiple data-driven missing imputation Unresolved cited work

Reference 98

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f71920da-2a75-408c-8385-36eac29ec2bb · outbound

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Multiple data-driven missing imputation Unresolved cited work

Reference 443

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

Observation 10c4d71c-440d-409b-bd0c-caf51effe283 · inbound

Hybrid activation functions for deep neural networks: S3 and S4 -- a novel approach to gradient flow optimization cites this paper.

Hybrid activation functions for deep neural networks: S3 and S4 -- a novel approach to gradient flow optimization Multiple data-driven missing imputation

Reference 25

Resolution
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