Paper Citation Record · LEDGER

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2502.03245.

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

pith.paper-citation-record.v1
2502.03245 v2

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:25:21.124116Z

measured 20 of 20 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 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

20 of 20 outbound references displayed

verified exact0
verified fuzzy19
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ccb7bca-91b2-4d6e-a0e5-be795e0d697f · outbound

This paper cites Anomaly detection on time series,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Anomaly detection on time series,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.452756Z

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.

Observation 40c08298-e5d6-4733-aa01-29a364d3b24d · outbound

This paper cites Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T05:25:21.044157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78970b11-67cf-4581-a3ef-39c2e051d09e · outbound

This paper cites Outlier detection and missing value in seasonal ARIMA model using rainfall data,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Outlier detection and missing value in seasonal ARIMA model using rainfall data,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.426649Z

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.

Observation c28adb79-2a1c-41f5-be08-e87e553741dd · outbound

This paper cites Modeling data containing outliers using ARIMA additive outlier (ARIMA-AO),.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Modeling data containing outliers using ARIMA additive outlier (ARIMA-AO),

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.411060Z

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.

Observation 5aa432d8-d8ef-44f9-a359-279c42b174b8 · outbound

This paper cites A machine learning framework for network anomaly detection using SVM and GA,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning A machine learning framework for network anomaly detection using SVM and GA,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.392809Z

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.

Observation 9290ae7b-28b1-4302-afb5-8911c6d80b4d · outbound

This paper cites Anomaly detection based on machine learning: dimensionality reduction using PCA and classification using SVM,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Anomaly detection based on machine learning: dimensionality reduction using PCA and classification using SVM,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.375389Z

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.

Observation c11f787d-5023-4e59-854f-03abde708096 · outbound

This paper cites A novel anomaly detection method based on adaptive mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning A novel anomaly detection method based on adaptive mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.360283Z

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.

Observation 580c60c2-169a-4f80-bbc3-240f60166a26 · outbound

This paper cites Unsupervised anomaly detection in time series using LSTM-based autoencoders,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Unsupervised anomaly detection in time series using LSTM-based autoencoders,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.345117Z

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.

Observation 452d314d-82ec-45b8-951f-57077518d262 · outbound

This paper cites Long short term memory networks for anomaly detection in time series.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Long short term memory networks for anomaly detection in time series

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.330054Z

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.

Observation 7920d87f-7006-446f-b6dd-cc84bdc3056c · outbound

This paper cites Unsupervised anomaly detection with LSTM neural networks,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Unsupervised anomaly detection with LSTM neural networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.314389Z

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.

Observation 2644abb5-64e2-4349-95d0-61900dab0be6 · outbound

This paper cites Improved LSTM-based time-series anomaly detection in rail transit operation environments,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Improved LSTM-based time-series anomaly detection in rail transit operation environments,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.300197Z

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.

Observation fa4564d1-30dc-41ce-aae7-cbd5e2690c73 · outbound

This paper cites Improving lead time forecasting and anomaly detection for automotive spare parts with a combined CNN-LSTM approach,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Improving lead time forecasting and anomaly detection for automotive spare parts with a combined CNN-LSTM approach,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.284458Z

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.

Observation c3a6d673-d66d-496a-a19d-880101779738 · outbound

This paper cites Time-series anomaly detection with stacked transformer representations and 1D convolutional network,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Time-series anomaly detection with stacked transformer representations and 1D convolutional network,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.270532Z

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.

Observation 2b7c4f02-dd67-4a8a-990b-d934c79e7f9f · outbound

This paper cites Unsupervised anomaly detection.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Unsupervised anomaly detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.255528Z

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.

Observation a2a08643-5609-46df-aee7-559be9b9ca28 · outbound

This paper cites Unsupervised anomaly detection in time-series: An exten- sive evaluation and analysis of state-of-the-art methods,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Unsupervised anomaly detection in time-series: An exten- sive evaluation and analysis of state-of-the-art methods,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.239954Z

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.

Observation f7aaca4a-72c6-44c4-83be-2b573b67463e · outbound

This paper cites Aero-engines anomaly detection using an unsupervised Fisher autoencoder,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Aero-engines anomaly detection using an unsupervised Fisher autoencoder,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.221801Z

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.

Observation 95ba5414-497f-4dbd-8162-446cf5282cf4 · outbound

This paper cites Calibrated one-class classification for unsupervised time series anomaly detection,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning Calibrated one-class classification for unsupervised time series anomaly detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.207039Z

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.

Observation e9a8f151-ad60-4d63-a756-c1aa78e1005a · outbound

This paper cites A hybrid model based on discrete wavelet transform (DWT) and bidirectional recurrent neural networks for wind speed prediction,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning A hybrid model based on discrete wavelet transform (DWT) and bidirectional recurrent neural networks for wind speed prediction,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.192101Z

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.

Observation b07165e3-4190-434d-91ff-ae49bfb4bab1 · outbound

This paper cites LSTM-autoencoder-based anomaly detection for indoor air quality time-series data,.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning LSTM-autoencoder-based anomaly detection for indoor air quality time-series data,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.176983Z

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.

Observation 9178d679-5067-429d-ac7b-4dfdd1678c47 · outbound

This paper cites User’s guide for the commercial modular aero-propulsion system simulation (c-mapss),.

Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning User’s guide for the commercial modular aero-propulsion system simulation (c-mapss),

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:25:21.160461Z

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.

Pith citing papers

No inbound Pith citation observations are available.