Paper Citation Record · LEDGER

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting

As of 20 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.00590.

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

pith.paper-citation-record.v1
2505.00590 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:42:21.424100Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

44 of 44 outbound references displayed

verified exact2
verified fuzzy29
unresolved12
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80dc0449-9d7d-4942-8542-083230d4f6d8 · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:42:22.054854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 104c1937-4be7-4321-bba9-a087d96617bc · outbound

This paper cites Neural flows: Efficient alternative to neural odes.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Neural flows: Efficient alternative to neural odes

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:22.043939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b55617fb-36c9-40f0-9083-673ab32d4b4f · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:42:22.031454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b0d2465a-1152-46eb-8d34-e1b8ee372a4d · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:42:22.019433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cc103bfb-066e-472f-a8af-58f46dd2f99c · outbound

This paper cites Gru-ode-bayes: Continuous modeling of sporadically-observed time series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Gru-ode-bayes: Continuous modeling of sporadically-observed time series

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:22.006808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e262a1b-2671-4fdd-900f-f08b865556be · outbound

This paper cites Spectral temporal graph neural network for multivariate time-series forecasting.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Spectral temporal graph neural network for multivariate time-series forecasting

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.994533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 516378db-b4ce-41d7-aa45-de6245c5df97 · outbound

This paper cites Recurrent Neural Networks for Multivariate Time Series with Missing Values.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Recurrent Neural Networks for Multivariate Time Series with Missing Values

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.289582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d49ba9cb-18f1-4a29-8124-24247c8fe24a · outbound

This paper cites Neural ordinary differential equations.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Neural ordinary differential equations

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.983702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 243a963f-5bd7-415e-bf13-562f98f83afe · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:42:21.967446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96eca95e-bf3d-4161-b36d-b98bbf477713 · outbound

This paper cites ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.300729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09baeb16-b51b-4f77-bec1-349c12c7f3e8 · outbound

This paper cites Deep sparse rectifier neural networks.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Deep sparse rectifier neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.955542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cacef93a-ce31-44ed-b447-3539778f6009 · outbound

This paper cites Borgwardt.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Borgwardt

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.941913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 20ad9122-0348-4e4c-bdb5-71a6b7eb7790 · outbound

This paper cites Hu, elong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Hu, elong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.929872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4c8696b2-0f1c-423a-846c-ffd74afa0726 · outbound

This paper cites Crossgnn: Confronting noisy multivariate time series via cross interaction refine- ment.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Crossgnn: Confronting noisy multivariate time series via cross interaction refine- ment

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.917714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a6a74c69-6a11-402b-9be2-e8eb926af53a · outbound

This paper cites Pickett, and Varun Dutt.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Pickett, and Varun Dutt

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.906935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e92bde8-77de-4816-8845-640583059691 · outbound

This paper cites Kingma and Jimmy Ba.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Kingma and Jimmy Ba

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.896260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4eb4d54f-0843-454e-92ac-08f1ffbbdbb8 · outbound

This paper cites Towards long-term time-series forecasting: Feature, pattern, and distribution.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Towards long-term time-series forecasting: Feature, pattern, and distribution

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.885538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9eba9a94-5d5b-41fb-84c9-f3109e81ba3d · outbound

This paper cites Time Series Forecasting With Deep Learning: A Survey.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Time Series Forecasting With Deep Learning: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.330915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35d71f93-836a-42f5-9bc9-8820c7810ee7 · outbound

This paper cites itransformer: Inverted transformers are effective for time series forecasting.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting itransformer: Inverted transformers are effective for time series forecasting

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.874039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 84526c7b-9bd6-471c-9dab-3b967f97d797 · outbound

This paper cites Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.338830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2d14456-ca60-4d1c-88f7-e2ee6e9dd758 · outbound

This paper cites Vale, and José Silva.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Vale, and José Silva

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.854856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 862525eb-09ad-451b-acd2-432c12bc67f9 · outbound

This paper cites Latent ordinary differential equations for irregularly-sampled time series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Latent ordinary differential equations for irregularly-sampled time series

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.842780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation afcee5c5-4f58-45ff-bb2d-b3d9daedead9 · outbound

This paper cites Modeling irregular time series with continuous recurrent units.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Modeling irregular time series with continuous recurrent units

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.830666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fadd042d-8c1d-4593-b502-fe90b2edf023 · outbound

This paper cites A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.352270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eab36a5-34fb-4238-afcc-48122648ad3a · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:42:21.818470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 371769f8-5304-4aea-9ca2-12886de3da8d · outbound

This paper cites An analysis of linear time series forecasting models.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting An analysis of linear time series forecasting models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.805811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5bb4e00c-02d5-489c-98f3-2754defac979 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.795034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e81bed09-3ae6-4dd3-962d-7a7d1df1ef82 · outbound

This paper cites Rethinking the power of timestamps for robust time series forecasting: A global-local fusion perspective.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Rethinking the power of timestamps for robust time series forecasting: A global-local fusion perspective

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.783769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 507b0dc7-a9ec-4a6c-9058-e357f7540e5c · outbound

This paper cites Timesnet: Temporal 2d-variation modeling for general time series analysis.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Timesnet: Temporal 2d-variation modeling for general time series analysis

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.371433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99c70d8e-f6cf-4f6b-a1a4-f3781bcbb9cc · outbound

This paper cites Not only pairwise relationships: Fine-grained relational modeling for multivariate time series forecasting.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Not only pairwise relationships: Fine-grained relational modeling for multivariate time series forecasting

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.764148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7d8c04c0-0bc7-4aa3-8532-e6529532ce97 · outbound

This paper cites Graph wavenet for deep spatial-temporal graph modeling.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Graph wavenet for deep spatial-temporal graph modeling

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.753579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68fd1183-9c90-46de-b3f1-805039824f83 · outbound

This paper cites Connecting the dots: Multivariate time series forecasting with graph neural networks.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Connecting the dots: Multivariate time series forecasting with graph neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.744052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6a5c75eb-c512-48b8-9ad8-75e01471ed85 · outbound

This paper cites Grafiti: Graphs for forecasting irregularly sampled time series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Grafiti: Graphs for forecasting irregularly sampled time series

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.732253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cd43c76-47ff-4203-b74b-fb59f45600c8 · outbound

This paper cites Fouriergnn: Rethinking multivariate time series forecasting from a pure graph perspective.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Fouriergnn: Rethinking multivariate time series forecasting from a pure graph perspective

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.719487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 85ce336e-694d-4b26-85e8-c7b0f89b5536 · outbound

This paper cites Is Channel Independent strategy optimal for Time Series Forecasting?.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Is Channel Independent strategy optimal for Time Series Forecasting?

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:42:21.570638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 241bd158-99ae-43b3-9e99-37a20100c0ef · outbound

This paper cites Are transformers effective for time series forecasting? In AAAI Conference on Artificial Intelligence, 2023.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Are transformers effective for time series forecasting? In AAAI Conference on Artificial Intelligence, 2023

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:21.396032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acf2248f-8ca1-4846-bb73-430a687df601 · outbound

This paper cites Warpformer: A multi-scale modeling approach for irregular clinical time series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Warpformer: A multi-scale modeling approach for irregular clinical time series

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.699727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 85b90fe1-d71f-4c91-b383-2587c238f370 · outbound

This paper cites Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:42:21.547790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 455b7ea6-0c20-47e3-9926-c5ff6d5ffc06 · outbound

This paper cites Irregular multivari- ate time series forecasting: A transformable patching graph neural networks approach.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Irregular multivari- ate time series forecasting: A transformable patching graph neural networks approach

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.687641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 85ee050d-143c-4fb3-bd06-40590874b26c · outbound

This paper cites Irregular traffic time series forecasting based on asynchronous spatio-temporal graph convolutional networks.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Irregular traffic time series forecasting based on asynchronous spatio-temporal graph convolutional networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.674789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7b49a80c-5255-4e52-a383-ba77653d00ec · outbound

This paper cites Graph-guided network for irregularly sampled multivariate time series.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Graph-guided network for irregularly sampled multivariate time series

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.664072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96a1bb63-f450-459f-94c7-25894dd8ef95 · outbound

This paper cites Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.650206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6269413d-0363-4a5c-9982-1bf4112be3fe · outbound

This paper cites Rethinking channel dependence for multivariate time series forecasting: Learning from leading indicators.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Rethinking channel dependence for multivariate time series forecasting: Learning from leading indicators

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:42:21.635112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e895943c-91db-4c21-b62b-1a80a7959b19 · outbound

This paper cites Forecasting fine-grained air quality based on big data.

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting Forecasting fine-grained air quality based on big data

Reference 44

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T04:42:21.527146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.