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Paper Citation Record · LEDGER

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.21357.

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

pith.paper-citation-record.v1
2507.21357 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:00:57.892462Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

40 of 40 outbound references displayed

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  • verified fuzzy38
  • unresolved1
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  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 463760e8-c157-42a1-a967-194e2652cbb9 · outbound

This paper cites Card: Classification and regression diffusion models.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Card: Classification and regression diffusion models

Reference 1

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Observation 15b4d995-a18e-4c45-872d-12e1e38127c6 · outbound

This paper cites shapeDTW: Shape dynamic time warping.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification shapeDTW: Shape dynamic time warping

Reference 2

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Observation 928773d3-e07a-4c85-aaa2-83ad7de541de · outbound

This paper cites catch22: CAnonical Time-series CHaracteristics.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification catch22: CAnonical Time-series CHaracteristics

Reference 3

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Observation 6a930217-269e-470a-8586-ace9e86e8f33 · outbound

This paper cites Scalable dictionary classifiers for time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Scalable dictionary classifiers for time series classification

Reference 4

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Observation faba817d-8c04-4e2c-aaf4-77aba5f35cdc · outbound

This paper cites Fast and accurate time series classification with weasel.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Fast and accurate time series classification with weasel

Reference 5

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Source-reported events for the cited work

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Observation 9847f032-af06-4d0b-bab5-3bd940c6844d · outbound

This paper cites HIVE-COTE 2.0: A new meta ensemble for time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification HIVE-COTE 2.0: A new meta ensemble for time series classification

Reference 6

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Observation 1d5b481f-dfcc-42d9-a0e5-b232a89993ac · outbound

This paper cites MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification

Reference 7

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Observation f1795e7d-26d5-4941-a216-84b388aec94d · outbound

This paper cites Fast and accurate time series classification through supervised interval search.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Fast and accurate time series classification through supervised interval search

Reference 8

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Source-reported events for the cited work

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Observation 31373a9f-d621-4d1b-a3d1-39e4cd1752e7 · outbound

This paper cites The freshprince: A simple transformation based pipeline time series classifier.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification The freshprince: A simple transformation based pipeline time series classifier

Reference 9

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Source-reported events for the cited work

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Observation 634f416b-ff5b-45f4-84e6-17a3eaec1b80 · outbound

This paper cites SFA: A symbolic fourier approximation and index.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification SFA: A symbolic fourier approximation and index

Reference 10

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Observation 5d5264bb-b2a0-4d84-9883-9ed806aa2779 · outbound

This paper cites Time series feature extraction using scalable hypothesis tests.Neurocomputing, 307:72–77, 2018.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Time series feature extraction using scalable hypothesis tests.Neurocomputing, 307:72–77, 2018

Reference 11

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Observation 944d0507-3942-4f23-afc1-a84bd9a08af3 · outbound

This paper cites Self-supervised learning for semi-supervised time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Self-supervised learning for semi-supervised time series classification

Reference 12

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Observation 46dc4b52-c63a-4bc7-b072-70ce31b61508 · outbound

This paper cites Self-supervised contrastive representation learning for semi-supervised time-series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Self-supervised contrastive representation learning for semi-supervised time-series classification

Reference 13

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Observation 2cfcd8bb-ad22-4866-bd3b-20908439f1ce · outbound

This paper cites Barlow twins: Self-supervised learning via redundancy reduction.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Barlow twins: Self-supervised learning via redundancy reduction

Reference 14

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Observation fbcc53d3-9184-4d9d-868c-5810eaccc7a0 · outbound

This paper cites Bootstrap your own latent: A new approach to self-supervised learning.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Bootstrap your own latent: A new approach to self-supervised learning

Reference 15

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Observation 7bba4a1d-2598-43f3-8815-44960d67556e · outbound

This paper cites The UCR time series archive.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification The UCR time series archive

Reference 16

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Source-reported events for the cited work

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Observation e7e375f5-3239-4dde-81a2-a46e73288584 · outbound

This paper cites Diffusion models in vision: A survey.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Diffusion models in vision: A survey

Reference 17

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Observation f2c06d22-e7b5-46d3-ac65-15f3b2fe9fbf · outbound

This paper cites InceptionTime: Finding AlexNet for time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification InceptionTime: Finding AlexNet for time series classification

Reference 18

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Observation d95a9f12-2f35-405d-98c7-aca98a7bc1fd · outbound

This paper cites Convolutional neural networks for time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Convolutional neural networks for time series classification

Reference 19

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Observation 4e373f00-8a27-43ac-811c-9be540279982 · outbound

This paper cites Multivariate LSTM-FCNs for time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Multivariate LSTM-FCNs for time series classification

Reference 20

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Source-reported events for the cited work

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Observation 27b96663-ce8c-4e28-86b0-29ce4862abdb · outbound

This paper cites Deep learning for time series classification: a review.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Deep learning for time series classification: a review

Reference 21

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Observation 794ca473-8d77-497c-a68c-58d0674c6141 · outbound

This paper cites Scalable diverse model selection for accessible transfer learning.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Scalable diverse model selection for accessible transfer learning

Reference 22

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Observation f27b6c5a-211e-4127-b2ed-27e6be4f1fae · outbound

This paper cites Time-series forecasting with deep learning: a survey.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Time-series forecasting with deep learning: a survey

Reference 23

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Observation 021cee3e-cce5-4437-b0f2-cc353f4d8755 · outbound

This paper cites Machine learning advances for time series forecasting.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Machine learning advances for time series forecasting

Reference 24

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Observation 5b1fe7cb-902e-4031-95bb-bc628fcf6776 · outbound

This paper cites An examination of the state-of-the-art for multivariate time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification An examination of the state-of-the-art for multivariate time series classification

Reference 25

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Observation 738e9ad4-9d7e-481a-afff-86052a267813 · outbound

This paper cites Using dynamic time warping to find patterns in time series.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Using dynamic time warping to find patterns in time series

Reference 26

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Observation 05002396-b088-4d10-a854-6a4092239d84 · outbound

This paper cites CNN approaches for time series classification.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification CNN approaches for time series classification

Reference 27

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Observation 4c91d861-3c15-46c7-a3a6-f734bfcc924e · outbound

This paper cites Scalable classification of univariate and multi- variate time series.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Scalable classification of univariate and multi- variate time series

Reference 28

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Observation 4447ef2c-6b8a-4ac4-bb94-4d4b53c8a8c9 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Diffusion models: A comprehensive survey of methods and applications

Reference 29

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Observation cae481c9-675c-4ebe-a06e-d9d84a526a97 · outbound

This paper cites A survey on deep semi-supervised learning.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification A survey on deep semi-supervised learning

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 45605963-0f7a-4d40-920a-48665b87f63a · outbound

This paper cites Denoising diffusion probabilistic models.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Denoising diffusion probabilistic models

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0e3db925-c6fd-4b83-9bb0-cb6e145b122c · outbound

This paper cites Error bounds for approximations with deep ReLU networks.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Error bounds for approximations with deep ReLU networks

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c1dc7bdf-dda7-4305-b903-ab4bbc4e2b7b · outbound

This paper cites Self-improvement of weighted pointwise inequalities on open sets.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Self-improvement of weighted pointwise inequalities on open sets

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c872ba34-8d86-4d5a-9e9e-bb05f0818235 · outbound

This paper cites Multi-task learning using uncertainty to weigh losses.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Multi-task learning using uncertainty to weigh losses

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d114b2d2-8bd4-4999-b143-bcc6e445f74c · outbound

This paper cites Finding order in chaos: A novel data augmentation method for time series in contrastive learning.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Finding order in chaos: A novel data augmentation method for time series in contrastive learning

Reference 36

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e83fdb2e-1c4d-42b8-9284-35dcc758ed86 · outbound

This paper cites Time-Series Representation Learning via Temporal and Contextual Contrasting.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Time-Series Representation Learning via Temporal and Contextual Contrasting

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T13:00:57.513885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7cd3443f-1b0c-493f-9010-35f336c0f64f · outbound

This paper cites Time-series representation learning via temporal and contextual contrasting.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Time-series representation learning via temporal and contextual contrasting

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:00:59.199219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fbdfbabe-0eaa-4b2b-a115-c99ddd3f5861 · outbound

This paper cites TS-TCC: Time-series representation learning via temporal and contextual contrasting.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification TS-TCC: Time-series representation learning via temporal and contextual contrasting

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:00:58.733417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e871d527-a45c-4578-8abc-fbc593fb1454 · outbound

This paper cites TS2Vec: Towards universal representation of time series.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification TS2Vec: Towards universal representation of time series

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:00:58.537787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7bda7e62-be8b-4d09-a33c-ab9f1f1961df · outbound

This paper cites Augmentations for self-supervised time-series representation learning.

A Contrastive Diffusion-based Network (CDNet) for Time Series Classification Augmentations for self-supervised time-series representation learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:00:58.342544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.