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Paper Citation Record · LEDGER

Revisiting PCA for time series reduction in temporal dimension

As of 12 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2412.19423.

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pith.paper-citation-record.v1
2412.19423 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

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measured 23 of 23 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

23 of 23 outbound references displayed

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External citation measurements

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Outbound references

Observation d2883b56-f659-4a6a-acc2-55d94c74c210 · outbound

This paper cites Transformers in Time Series: A Survey.

Revisiting PCA for time series reduction in temporal dimension Transformers in Time Series: A Survey

Reference 6

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This paper cites Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting.

Revisiting PCA for time series reduction in temporal dimension Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting

Reference 7

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This paper cites Table 8: TSC experiments on the UCR datasets.

Revisiting PCA for time series reduction in temporal dimension Table 8: TSC experiments on the UCR datasets

Reference 8

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Observation d1ce1ed3-0bbc-414c-9008-dd7d85a31a09 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Revisiting PCA for time series reduction in temporal dimension Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 9

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Observation 003f7941-d969-451a-a39d-068e0d5de7e4 · outbound

This paper cites SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters.

Revisiting PCA for time series reduction in temporal dimension SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

Reference 11

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Observation c7271895-478a-4e18-89f7-f5b4dc749d52 · outbound

This paper cites Word Emdeddings through Hellinger PCA.

Revisiting PCA for time series reduction in temporal dimension Word Emdeddings through Hellinger PCA

Reference 12

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Observation 51c8cac3-3934-4cf9-82d2-3fae7e4bc9a1 · outbound

This paper cites How Many Components should be Retained from a Multivariate Time Series PCA?.

Revisiting PCA for time series reduction in temporal dimension How Many Components should be Retained from a Multivariate Time Series PCA?

Reference 13

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Observation aa3931a5-73f3-48c8-b82b-94c03568eb51 · outbound

This paper cites Vector Quantized Time Series Generation with a Bidirectional Prior Model.

Revisiting PCA for time series reduction in temporal dimension Vector Quantized Time Series Generation with a Bidirectional Prior Model

Reference 16

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Observation 664b96b4-e20b-4086-a0a5-44885f0df9b9 · outbound

This paper cites Revisiting PCA for Time Series Reduction in Temporal Dimension.

Revisiting PCA for time series reduction in temporal dimension Revisiting PCA for Time Series Reduction in Temporal Dimension

Reference 17

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Observation a7af3fa9-f3cc-401a-9ebd-0da4a7cf1d26 · outbound

This paper cites oil temperature.

Revisiting PCA for time series reduction in temporal dimension oil temperature

Reference 18

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This paper cites The accuracy metric is adopted.

Revisiting PCA for time series reduction in temporal dimension The accuracy metric is adopted

Reference 23

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Revisiting PCA for time series reduction in temporal dimension Unresolved cited work

Reference 84

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Observation 37a0dcdd-bc46-4c84-a31f-73dfd51bda59 · outbound

This paper cites • FloodModeling [Tan et al., 2021]: FloodModeling comprises three hourly datasets (FloodModeling1, Flood- Modeling2, and FloodModeling3).

Revisiting PCA for time series reduction in temporal dimension • FloodModeling [Tan et al., 2021]: FloodModeling comprises three hourly datasets (FloodModeling1, Flood- Modeling2, and FloodModeling3)

Reference 315

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This paper cites SelfRegulationSCP2 comprises 380 series samples, each with a length of 1,152.

Revisiting PCA for time series reduction in temporal dimension SelfRegulationSCP2 comprises 380 series samples, each with a length of 1,152

Reference 896

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Observation f298f34b-c1c1-4608-b866-a54e71801049 · outbound

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

Revisiting PCA for time series reduction in temporal dimension Fast and accurate time series classification with weasel

Reference 2009

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Observation accc6e7d-298e-49f3-b3fd-6d9dc590426a · outbound

This paper cites Ailing Zeng, Muxi Chen, Lei Zhang, and Qiang Xu.

Revisiting PCA for time series reduction in temporal dimension Ailing Zeng, Muxi Chen, Lei Zhang, and Qiang Xu

Reference 2015

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Observation a2b6ea11-8e31-4239-865e-7892f58dfbba · outbound

This paper cites Fredformer: Frequency Debiased Transformer for Time Series Forecasting.

Revisiting PCA for time series reduction in temporal dimension Fredformer: Frequency Debiased Transformer for Time Series Forecasting

Reference 2017

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Observation db5b63a5-1755-4249-ae1e-4db48ad78363 · outbound

This paper cites The UEA multivariate time series classification archive, 2018.

Revisiting PCA for time series reduction in temporal dimension The UEA multivariate time series classification archive, 2018

Reference 2018

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This paper cites Inceptiontime: Finding alexnet for time series classification.

Revisiting PCA for time series reduction in temporal dimension Inceptiontime: Finding alexnet for time series classification

Reference 2019

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Observation 6ceebbb4-30cf-41ba-a70b-9d01989933cf · outbound

This paper cites Transformer Multivariate Forecasting: Less is More?.

Revisiting PCA for time series reduction in temporal dimension Transformer Multivariate Forecasting: Less is More?

Reference 2021

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Observation 04f8c7ac-5a8e-4a2a-8963-fe48d3b8a90a · outbound

This paper cites MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing.

Revisiting PCA for time series reduction in temporal dimension MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing

Reference 2022

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Observation 75f105e2-2cf0-4b98-ac27-e220beb4deb3 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Revisiting PCA for time series reduction in temporal dimension A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 2023

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This paper cites TSLANet: Rethinking Transformers for Time Series Representation Learning.

Revisiting PCA for time series reduction in temporal dimension TSLANet: Rethinking Transformers for Time Series Representation Learning

Reference 2024

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