Paper Citation Record · LEDGER

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series

As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2508.11528.

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

pith.paper-citation-record.v1
2508.11528 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:56:10.982333Z

measured 32 of 32 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:37:40.632230Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy17
unresolved12
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dba48e7b-50f6-4dec-a3ad-bb8914d4b3ed · outbound

This paper cites Janot, M.G., Brunot, M.: Data set and reference models of emps.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Janot, M.G., Brunot, M.: Data set and reference models of emps

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.363606Z

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Observation 62421ddc-4f76-4b69-9ab7-ca6dbbbd1ba7 · outbound

This paper cites Physics-Informed Diffusion Models.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Physics-Informed Diffusion Models

Reference 2

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Observation ee9de46a-e7bf-4676-a04d-238670fdb9eb · outbound

This paper cites an unresolved cited work.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:56:11.353549Z

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Observation 0c991da6-7151-4146-beff-9a13cf690787 · outbound

This paper cites Journal of the American statistical Association 112(518), 859–877 (2017).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Journal of the American statistical Association 112(518), 859–877 (2017)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.344633Z

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Observation 921d7759-ac82-4aef-abcc-83401c188f35 · outbound

This paper cites ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T19:56:10.910977Z

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Observation 3d81cbbe-712b-41e6-a83a-a4583da03379 · outbound

This paper cites Constrained Synthesis with Projected Diffusion Models.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Constrained Synthesis with Projected Diffusion Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T19:56:10.913973Z

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Observation 97caee28-2f9c-4130-966c-307bfe95dddd · outbound

This paper cites an unresolved cited work.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Unresolved cited work

Reference 7

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Observation af4d32a8-01ae-43ba-bcdd-6c697605ac9b · outbound

This paper cites TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T19:56:10.919947Z

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Observation e9bf98e4-15ee-4f3e-a67a-c39cd9606368 · outbound

This paper cites an unresolved cited work.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Unresolved cited work

Reference 9

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Source-reported events for the cited work

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Observation 54059f95-cd3d-4e42-ad40-49cf608c568c · outbound

This paper cites In: Asian Conference on Machine Learning.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: Asian Conference on Machine Learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.319388Z

Source-reported events for the cited work

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Observation 1bc098d9-3eef-4783-bb29-c107b3ec4cc7 · outbound

This paper cites In: 2021 IEEE 17th International Conference on Automation Science and Engi- neering (CASE).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: 2021 IEEE 17th International Conference on Automation Science and Engi- neering (CASE)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.309525Z

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 ca77a2f0-5372-407c-8218-f31e06a6c9f1 · outbound

This paper cites Advances in neural information processing systems33, 6840–6851 (2020).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Advances in neural information processing systems33, 6840–6851 (2020)

Reference 12

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Observation 60980f66-c998-4996-98a5-1417d11d2241 · outbound

This paper cites Scholarpedia1(10), 1563 (2006).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Scholarpedia1(10), 1563 (2006)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.294340Z

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 01972616-0200-48a7-b4d0-f29157540c82 · outbound

This paper cites In: ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.285768Z

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 f0277a39-24b0-47fc-bdef-9ca00cecdb43 · outbound

This paper cites CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems

Reference 15

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Observation b816162c-9b29-492d-bd46-0c10ec76466c · outbound

This paper cites IEEE Access 7, 143608–143619 (2019).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series IEEE Access 7, 143608–143619 (2019)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.277151Z

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 3f77451a-169a-43e4-a9e5-a6d6346e8075 · outbound

This paper cites Advances in neural information processing systems34, 21696–21707 (2021).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Advances in neural information processing systems34, 21696–21707 (2021)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.268495Z

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 fa7c31a3-e840-4dc9-9dfe-081086dbf887 · outbound

This paper cites an unresolved cited work.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Unresolved cited work

Reference 18

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Source-reported events for the cited work

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Observation d95d35a8-68f3-4391-afda-0c01ea9be2fc · outbound

This paper cites an unresolved cited work.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Unresolved cited work

Reference 19

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Source-reported events for the cited work

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Observation b8be3e81-2e3d-436c-af1a-d6f577f1b42e · outbound

This paper cites In: Interna- tional conference on artificial neural networks.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: Interna- tional conference on artificial neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.242251Z

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 04b1d82f-2c0e-4ac1-b2d7-64489af3f7bc · outbound

This paper cites In: ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.234000Z

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 e84cc815-70a2-4466-8707-fea858e72365 · outbound

This paper cites Machine Learning for Computational Science and Engineering1(1), 1–23 (2025).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Machine Learning for Computational Science and Engineering1(1), 1–23 (2025)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.224175Z

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 adfbf9e5-ec36-42b3-b3b1-35bb3243d27d · outbound

This paper cites In: 2020 IEEE Power & Energy Society General Meeting (PESGM).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: 2020 IEEE Power & Energy Society General Meeting (PESGM)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.215215Z

Source-reported events for the cited work

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Observation ae29a115-6253-46e5-93e0-00158ae18b71 · outbound

This paper cites Engineering Applications of Arti- ficial Intelligence 131, 107696 (2024).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Engineering Applications of Arti- ficial Intelligence 131, 107696 (2024)

Reference 24

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Observation d3d3558f-78a5-4335-b13e-68e0a38d608e · outbound

This paper cites MIT Press (2022), probml.ai.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series MIT Press (2022), probml.ai

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.205368Z

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 5d8ac42c-4f01-4144-a802-fcde64cd2327 · outbound

This paper cites MIT Press (2023), http://probml.github.io/book2.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series MIT Press (2023), http://probml.github.io/book2

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.196451Z

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 5a025a96-e2c1-4dec-9370-c5b8a3fc5473 · outbound

This paper cites In: International Conference on Machine Learning.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: International Conference on Machine Learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.187440Z

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 91f572e3-7904-41ee-bf70-b5e73eb2307e · outbound

This paper cites Sensors 20(13), 3738 (2020).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Sensors 20(13), 3738 (2020)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.178634Z

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 d74fe7c6-410a-4fe2-87e7-9538b86aa7c3 · outbound

This paper cites In: 2023 IEEE International Conference on Data Mining Workshops (ICDMW).

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series In: 2023 IEEE International Conference on Data Mining Workshops (ICDMW)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:56:11.169511Z

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 edcd5777-16e7-4f3d-bb93-5ce5637389c6 · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 30

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Source-reported events for the cited work

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Observation e5e1bfe0-2fe2-4519-a927-61b21664b169 · outbound

This paper cites Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T19:56:10.982333Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation aadad655-aa67-49a1-9415-866568fb7f75 · inbound

Integrating Fourier Neural Operator with Diffusion Model for Autoregressive Predictions of Three-dimensional Turbulence cites this paper.

Integrating Fourier Neural Operator with Diffusion Model for Autoregressive Predictions of Three-dimensional Turbulence Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-03T16:37:40.632230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.