Paper Citation Record · LEDGER

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection

As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2508.16034.

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

pith.paper-citation-record.v1
2508.16034 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:39:21.344020Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

22 of 22 outbound references displayed

verified exact1
verified fuzzy10
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c4971149-0252-4706-a656-d2a3c001441b · outbound

This paper cites Mvtec ad–a comprehensive real- world dataset for unsupervised anomaly detection.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Mvtec ad–a comprehensive real- world dataset for unsupervised anomaly detection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:19.339869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 463a3cdf-c0ee-48d8-a92b-8cd048b6a7d1 · outbound

This paper cites PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:19.453081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75e592a5-1d79-45e5-90ec-b4b99f4d12af · outbound

This paper cites A theory for multiresolution signal decomposition: The wavelet representation.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection A theory for multiresolution signal decomposition: The wavelet representation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:24.015411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 853e0873-0686-49c4-b1e9-8bbb89c39515 · outbound

This paper cites Deep residual learning for image recognition.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Deep residual learning for image recognition

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:19.709439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30f5cb5f-5397-4420-adbc-50e0fd95bdbe · outbound

This paper cites an unresolved cited work.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-05T17:39:23.842272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation edc43afe-53b5-4e83-9d42-3509e49331d1 · outbound

This paper cites Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:19.941879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4da3408d-027c-408a-8bb6-1789cc1c542b · outbound

This paper cites Memorizing normality to de- tect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Memorizing normality to de- tect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:23.706272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f90d7cda-9a4d-4779-9632-a50172583184 · outbound

This paper cites Wald- stein, Ursula Schmidt-Erfurth, and Georg Langs.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Wald- stein, Ursula Schmidt-Erfurth, and Georg Langs

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:23.509638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 52b5205f-952f-475e-a1e8-e749c4e4483f · outbound

This paper cites an unresolved cited work.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-05T17:39:23.392557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9fa67ab-b871-4d13-9ad5-6ae98c1ef901 · outbound

This paper cites Sub-image anomaly detection with deep pyramid correspondences.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Sub-image anomaly detection with deep pyramid correspondences

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:23.262639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca95dbfc-99d1-48fa-b1ae-1b290a7f4a34 · outbound

This paper cites Towards Total Recall in Industrial Anomaly Detection.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Towards Total Recall in Industrial Anomaly Detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:20.434011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9aed30d-1efe-4b6a-b8da-2c4ed9af0849 · outbound

This paper cites Uninformed stu- dents: Student–teacher anomaly detection with dis- criminative latent embeddings.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Uninformed stu- dents: Student–teacher anomaly detection with dis- criminative latent embeddings

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:23.122314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 165d14f7-7bf0-4a25-adf6-67bb4a5e045a · outbound

This paper cites Cut- paste: Self-supervised learning for anomaly detection and localization.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Cut- paste: Self-supervised learning for anomaly detection and localization

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:22.963685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ede6c57-2747-4e79-8494-7b5d24bc11d6 · outbound

This paper cites Fastflow: Un- supervised anomaly detection and localization via 2d normalizing flows.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Fastflow: Un- supervised anomaly detection and localization via 2d normalizing flows

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:20.642520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4f46c1e-fbfe-4749-b8d6-f7c129c3ff86 · outbound

This paper cites Draem: A discriminative reconstruction autoencoder for weakly-supervised anomaly detection.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Draem: A discriminative reconstruction autoencoder for weakly-supervised anomaly detection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:22.857096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9201998c-cbe1-4916-b565-46c803fb7f2a · outbound

This paper cites Simulation study on the fleet performance of shared autonomous bicycles.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Simulation study on the fleet performance of shared autonomous bicycles

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T17:39:22.146787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cb285f87-e20e-4bc0-9c9f-7b9e63e517ea · outbound

This paper cites Light padim for unsupervised defect detection and location.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Light padim for unsupervised defect detection and location

Reference 17

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T17:39:21.991562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7b253ed-ce62-41cd-a1c2-f3c93cbcbe5f · outbound

This paper cites Patch distribution modeling framework adaptive cosine estimator (PaDiM-ACE) for anomaly detection and localization in synthetic aperture radar imagery.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Patch distribution modeling framework adaptive cosine estimator (PaDiM-ACE) for anomaly detection and localization in synthetic aperture radar imagery

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-05T17:39:21.642345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e3eb1e3-79d5-4474-87ff-6472ec1314ad · outbound

This paper cites Group invariant scattering.Com- munications on Pure and Applied Mathematics, 65 (10):1331–1398, 2012.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Group invariant scattering.Com- munications on Pure and Applied Mathematics, 65 (10):1331–1398, 2012

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:22.727099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8234e27a-32a8-429c-a6b7-5b728727eed6 · outbound

This paper cites Anomaly detection in time series data using a combination of wavelets, neural networks and hilbert transform.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Anomaly detection in time series data using a combination of wavelets, neural networks and hilbert transform

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:22.553403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3409f201-db70-4105-8cf3-3b5a75e861f5 · outbound

This paper cites De-noising by soft-thresholding.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection De-noising by soft-thresholding

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:21.279637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59cdeb36-269e-48be-a669-e5968b7c0f67 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning li- brary.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection Pytorch: An imperative style, high-performance deep learning li- brary

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:39:22.449705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.