ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting | Paper Citation Record

Observation f65569cc-aed2-43de-ba03-6f1c5d4bf280 · outbound

This paper cites A spatio-temporal diffusion model for missing and real-time financial data inference,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting A spatio-temporal diffusion model for missing and real-time financial data inference,

Reference 1

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Observation b4ec7f2e-04a7-4d73-b4bf-e30198e3be97 · outbound

This paper cites Extreme-aware local-global attention for spatio-temporal urban mobility learning,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Extreme-aware local-global attention for spatio-temporal urban mobility learning,

Reference 2

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Observation 657f026a-8544-4cbc-94b6-d0ae65ac07a2 · outbound

This paper cites Dynamic frequency domain graph convolutional network for traffic forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Dynamic frequency domain graph convolutional network for traffic forecasting,

Reference 3

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This paper cites Sta-gann: A valid and generalizable spatio-temporal kriging approach,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Sta-gann: A valid and generalizable spatio-temporal kriging approach,

Reference 4

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Observation 426a5baf-ea37-492d-b953-dda16d340af0 · outbound

This paper cites Shape analysis for time series,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Shape analysis for time series,

Reference 5

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Observation 637ba995-fdd5-4df6-a94d-cebed928c82e · outbound

This paper cites Exploring progress in multivariate time series forecasting: Comprehensive benchmarking and heterogeneity analysis,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Exploring progress in multivariate time series forecasting: Comprehensive benchmarking and heterogeneity analysis,

Reference 6

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Observation a53ace97-5a7a-479e-a07c-5d5bb652f024 · outbound

This paper cites Tfb: Towards comprehensive and fair benchmarking of time series forecasting methods,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Tfb: Towards comprehensive and fair benchmarking of time series forecasting methods,

Reference 7

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Observation 9a1cf860-ca9e-4324-bbfb-0e2b9229ad4e · outbound

This paper cites A Survey of Deep Learning and Foundation Models for Time Series Forecasting.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting A Survey of Deep Learning and Foundation Models for Time Series Forecasting

Reference 8

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Observation b5744ba5-f149-42df-a2ee-e238befebecc · outbound

This paper cites Deep time series models: A comprehensive survey and benchmark,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Deep time series models: A comprehensive survey and benchmark,

Reference 9

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Observation 02f4aae4-6599-4b5a-8afe-0569b1a7162a · outbound

This paper cites Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,

Reference 10

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Observation 8aa8b255-484d-4213-8b7b-0442b4170eed · outbound

This paper cites Fedformer: Frequency enhanced decomposed transformer for long-term series fore- casting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Fedformer: Frequency enhanced decomposed transformer for long-term series fore- casting,

Reference 11

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Observation 7f9be505-1504-41a5-a142-08cbba0ecd95 · outbound

This paper cites ETSformer: Exponential Smoothing Transformers for Time-series Forecasting.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Reference 12

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Observation 82bd10ce-15d9-4523-be80-10541dfdfcd3 · outbound

This paper cites Timemixer: Decomposable multiscale mixing for time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Timemixer: Decomposable multiscale mixing for time series forecasting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.623977Z

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Observation 40e7f280-a318-4d80-bda8-e1fab1886a3f · outbound

This paper cites Stl: A seasonal-trend decomposition,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Stl: A seasonal-trend decomposition,

Reference 14

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Observation b380cc3e-5f5e-4dbf-9d7c-b3893c6b98ed · outbound

This paper cites Reversible instance normalization for accurate time-series forecasting against dis- tribution shift,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Reversible instance normalization for accurate time-series forecasting against dis- tribution shift,

Reference 15

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Observation 791eb6ba-de46-4e61-9dab-a0f8dde792e3 · outbound

This paper cites Film: Frequency improved legendre memory model for long-term time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Film: Frequency improved legendre memory model for long-term time series forecasting,

Reference 16

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Observation f6632261-d614-4634-86c4-06654f039be8 · outbound

This paper cites Non-stationary transformers: Exploring the stationarity in time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Non-stationary transformers: Exploring the stationarity in time series forecasting,

Reference 17

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Observation ccaec986-8168-4050-b481-3888ff67b55a · outbound

This paper cites Dsformer: A double sampling transformer for multivariate time series long-term prediction,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Dsformer: A double sampling transformer for multivariate time series long-term prediction,

Reference 18

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Observation 2dcf3a45-22b7-498e-a65f-e30b12f0c62c · outbound

This paper cites itrans- former: Inverted transformers are effective for time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting itrans- former: Inverted transformers are effective for time series forecasting,

Reference 19

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Observation 6411c966-9b39-4425-a846-7058b770c4f6 · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting A time series is worth 64 words: Long-term forecasting with transformers,

Reference 20

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Observation 470057b7-8b85-4151-a706-3509a95ca465 · outbound

This paper cites Sparsetsf: Modeling long-term time series forecasting with* 1k* parameters,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Sparsetsf: Modeling long-term time series forecasting with* 1k* parameters,

Reference 21

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Observation 5d0262da-abc4-4f38-a5ee-aaa9818e22be · outbound

This paper cites SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 22

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Observation e0986ffc-17a3-4d63-b3ce-5fb1ff66080b · outbound

This paper cites U-mixer: An unet-mixer architecture with stationarity correction for time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting U-mixer: An unet-mixer architecture with stationarity correction for time series forecasting,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.555948Z

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Observation f31ceb4a-1797-40da-b6bf-1b32eb12da43 · outbound

This paper cites Position: There are no champions in long-term time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Position: There are no champions in long-term time series forecasting,

Reference 24

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Observation 9cb1bf7e-5808-4d80-98a5-6bd7d830c32e · outbound

This paper cites Deep Time Series Models: A Comprehensive Survey and Benchmark.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Deep Time Series Models: A Comprehensive Survey and Benchmark

Reference 25

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Observation 2d55f5e1-e05c-4f14-b013-a2438049e990 · outbound

This paper cites Monash time series forecasting archive,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Monash time series forecasting archive,

Reference 26

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Observation 6431a0a0-72f3-4c34-8bf6-a500e3d20f19 · outbound

This paper cites Probts: Benchmarking point and distributional forecasting across diverse pre- diction horizons,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Probts: Benchmarking point and distributional forecasting across diverse pre- diction horizons,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.539585Z

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Observation 90627f36-b496-425f-a7c0-c9bc4e8a730c · outbound

This paper cites GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

Reference 28

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Observation cf1cd9bf-b7bb-4432-ad11-3b6dc62703a5 · outbound

This paper cites TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting

Reference 29

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Observation 43a5a156-82e2-423b-b1d0-91c4fd61ab02 · outbound

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

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Timesnet: Temporal 2d-variation modeling for general time series analysis,

Reference 30

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Observation f4855d27-711c-4b4a-be36-6655e4959d63 · outbound

This paper cites Chronos: Learning the language of time series,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Chronos: Learning the language of time series,

Reference 31

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Observation 8886c75b-a8f7-4a1b-b75b-dfbafc73ebd7 · outbound

This paper cites Forecastpfn: Synthetically-trained zero-shot forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Forecastpfn: Synthetically-trained zero-shot forecasting,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.514216Z

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Observation 6304d23a-6ab8-4839-870f-e8af39f6edb1 · outbound

This paper cites Some recent advances in forecasting and control,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Some recent advances in forecasting and control,

Reference 33

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This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.500014Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 03c19bba-4036-4f3c-8da1-2de2a0ceef79 · outbound

This paper cites Distribution of the estimators for autoregressive time series with a unit root,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Distribution of the estimators for autoregressive time series with a unit root,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.491582Z

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Observation 1caf4971-0e7f-4145-877f-459c3c8cdfdd · outbound

This paper cites Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.483388Z

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Observation 88c13e33-7842-4bda-9be0-c6bda9f74dbf · outbound

This paper cites Moment: A family of open time-series foundation models,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Moment: A family of open time-series foundation models,

Reference 37

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Observation afd7a5db-0088-4f46-8f36-3b0e105bd218 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting A decoder-only foundation model for time-series forecasting

Reference 38

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This paper cites Hyndman, A.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Hyndman, A

Reference 39

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bcef1c31-a6ed-4cbd-9591-11f5441bfa91 · outbound

This paper cites Are transformers effective for time series forecasting?.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Are transformers effective for time series forecasting?

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.459392Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b050deb-4de4-43df-944b-376082fe6615 · outbound

This paper cites MSTL: A Seasonal-Trend Decomposition Algorithm for Time Series with Multiple Seasonal Patterns.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting MSTL: A Seasonal-Trend Decomposition Algorithm for Time Series with Multiple Seasonal Patterns

Reference 41

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Observation 3029ffc1-9b87-4e02-937c-c6dd8374102d · outbound

This paper cites Fred- former: Frequency debiased transformer for time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Fred- former: Frequency debiased transformer for time series forecasting,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.451006Z

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Observation 777ca6fa-91db-4656-964f-e1a326fba3cc · outbound

This paper cites Cyclenet: enhancing time series forecasting through modeling periodic patterns,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Cyclenet: enhancing time series forecasting through modeling periodic patterns,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.442454Z

Source-reported events for the cited work

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Observation 58913ff7-b4a1-40c2-a7d9-16c6aacc3406 · outbound

This paper cites Frequency-domain mlps are more effective learners in time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Frequency-domain mlps are more effective learners in time series forecasting,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.434603Z

Source-reported events for the cited work

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Observation 007b0d56-55c3-4a28-9057-66cd71855e1c · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent networks,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Deepar: Probabilistic forecasting with autoregressive recurrent networks,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.426415Z

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Observation a6fbc7c7-89f2-42bf-a15f-d410e7e9b769 · outbound

This paper cites Unified training of universal time series forecasting transformers,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Unified training of universal time series forecasting transformers,

Reference 46

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This paper cites Long- term forecasting with tide: Time-series dense encoder,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Long- term forecasting with tide: Time-series dense encoder,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.413428Z

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Observation 52c68403-01dd-407f-939b-c03750e5c99b · outbound

This paper cites Autoregressive conditional heteroscedasticity with es- timates of the variance of united kingdom inflation,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Autoregressive conditional heteroscedasticity with es- timates of the variance of united kingdom inflation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.405388Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a078ff2-7b05-4a95-b12d-3d0a1ec110f4 · outbound

This paper cites Gaussian processes for machine learning,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Gaussian processes for machine learning,

Reference 49

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Observation 0c053611-2c0d-4786-ac35-a64a9990cd34 · outbound

This paper cites BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-05T04:36:32.897610Z

Source-reported events for the cited work

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Observation 248b5905-0fa0-46c6-a12c-5697dc6ff5b6 · outbound

This paper cites Vii. on a method of investigating periodicities disturbed series, with special reference to wolfer’s sunspot numbers,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Vii. on a method of investigating periodicities disturbed series, with special reference to wolfer’s sunspot numbers,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.392415Z

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Observation b6521b31-02fc-4031-b4d1-1e4d3bb6d424 · outbound

This paper cites On periodicity in series of related terms,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting On periodicity in series of related terms,

Reference 52

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This paper cites The holt-winters forecasting procedure,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting The holt-winters forecasting procedure,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.379797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c9cad3a6-e4ac-47e7-a9de-e707a9e439cc · outbound

This paper cites A training algorithm for optimal margin classifiers,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting A training algorithm for optimal margin classifiers,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.372407Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8417e416-c403-4420-a204-4691cd5f9957 · outbound

This paper cites Catboost: unbiased boosting with categorical features,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Catboost: unbiased boosting with categorical features,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.365281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 58748e1f-b8cd-4cf3-af33-ce24b6c05e02 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Lightgbm: A highly efficient gradient boosting decision tree,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.357774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9dcf91c3-c6c1-4723-893b-79c25c1eb2ab · outbound

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

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Crossformer: Transformer utilizing cross- dimension dependency for multivariate time series forecasting,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.350242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ccf5b65e-d192-40fb-9c62-10fecb45fff7 · outbound

This paper cites Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.342562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 12f51511-ed29-4acf-b204-b5f4dcd63f32 · outbound

This paper cites Triformer: Triangular, variable-specific attentions for long sequence multivariate time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Triformer: Triangular, variable-specific attentions for long sequence multivariate time series forecasting,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.334632Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 188c725d-c2fc-49d8-b52d-d40b2c5d30e7 · outbound

This paper cites Are self-attentions effective for time series forecasting?.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Are self-attentions effective for time series forecasting?

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.326506Z

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Observation 825b9886-1b68-48df-a3a0-e3a8befa4cbe · outbound

This paper cites Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 61

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Observation f37d19b7-478f-4059-b43f-7714d94b3a3a · outbound

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

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T04:36:30.579715Z

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Observation ea8a71e6-5df4-42fb-8526-e1abea2c2829 · outbound

This paper cites N-beats: Neural basis expansion analysis for interpretable time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting N-beats: Neural basis expansion analysis for interpretable time series forecasting,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.318758Z

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Observation 29f1ef4d-80b8-456c-a1d0-0517ed13bc17 · outbound

This paper cites Nhits: Neural hierarchical interpolation for time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Nhits: Neural hierarchical interpolation for time series forecasting,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.311033Z

Source-reported events for the cited work

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Observation 71c56625-bcbc-413e-bdaa-209f724fce80 · outbound

This paper cites SOFTS: efficient multivariate time series forecasting with series-core fusion,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting SOFTS: efficient multivariate time series forecasting with series-core fusion,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.303862Z

Source-reported events for the cited work

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Observation aa155ca2-6128-4b97-b2a8-68c6ad958ec9 · outbound

This paper cites Spatial-temporal identity: A simple yet effective baseline for multivariate time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Spatial-temporal identity: A simple yet effective baseline for multivariate time series forecasting,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.295835Z

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Observation cc003a6e-3564-4f62-b87a-9ad6477c23e5 · outbound

This paper cites Time-moe: Billion-scale time series foundation models with mixture of experts,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Time-moe: Billion-scale time series foundation models with mixture of experts,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.287910Z

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Observation d453b833-bd55-4fd1-90eb-6b8e05bf3dec · outbound

This paper cites Historical inertia: A neglected but powerful baseline for long sequence time-series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Historical inertia: A neglected but powerful baseline for long sequence time-series forecasting,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.280773Z

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Observation 80077866-fc4a-45c1-baff-fc9364b784e4 · outbound

This paper cites Structured matrix basis for mul- tivariate time series forecasting with interpretable dynamics,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Structured matrix basis for mul- tivariate time series forecasting with interpretable dynamics,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.273524Z

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Observation ccccaa37-601c-4599-8185-5e43e88a1779 · outbound

This paper cites Wavenet: A generative model for raw audio,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Wavenet: A generative model for raw audio,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.265918Z

Source-reported events for the cited work

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Observation 1de9867f-7958-40fe-8fc3-d833d576b09b · outbound

This paper cites Frequency Adaptive Normalization For Non-stationary Time Series Forecasting.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Frequency Adaptive Normalization For Non-stationary Time Series Forecasting

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T04:36:31.595317Z

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Observation aecbba10-6055-4d5d-a928-2d736dd9152c · outbound

This paper cites The capacity and robustness trade-off: Revisiting the channel independent strategy for multivariate time series forecasting,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting The capacity and robustness trade-off: Revisiting the channel independent strategy for multivariate time series forecasting,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.258427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5800ce27-0629-4005-bf4d-e146a4d35a7a · outbound

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

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Rethinking channel dependence for multivariate time series forecasting: Learning from leading indicators,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.250967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36e6ad09-f68d-4227-8bda-c19eeb94bbc7 · outbound

This paper cites Discrete federated multi- behavior recommendation for privacy-preserving heterogeneous one- class collaborative filtering,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Discrete federated multi- behavior recommendation for privacy-preserving heterogeneous one- class collaborative filtering,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.242978Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11dc5bcc-992c-4709-9c8f-9cce06d35c94 · outbound

This paper cites Efficient k-nearest neighbor searching in nonordered discrete data spaces,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Efficient k-nearest neighbor searching in nonordered discrete data spaces,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.235615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69e7db27-710b-4b48-9228-c52df9709410 · outbound

This paper cites Structure discovery in nonparametric regression through compositional kernel search,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Structure discovery in nonparametric regression through compositional kernel search,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.227848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2c7296e3-b293-4e8a-9b26-962661ccb7d0 · outbound

This paper cites Fourier’s series,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Fourier’s series,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.220449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be2b9228-3e29-441a-8845-ccc19216114b · outbound

This paper cites The generalized weierstrass approximation theorem,.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting The generalized weierstrass approximation theorem,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.213230Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 19a75bf5-10aa-4ec7-a308-2e04a75b7ddb · outbound

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ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-05T04:36:33.205078Z

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Observation 732841b4-ea3c-405f-b590-a76b089cc990 · outbound

This paper cites The KPSS/ADF test [35] and ACF plot methods adopted in our test of stationarity are also the common strategies used in econometrics to determine strictly stationary se- ries.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting The KPSS/ADF test [35] and ACF plot methods adopted in our test of stationarity are also the common strategies used in econometrics to determine strictly stationary se- ries

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.197737Z

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Observation ca66653e-0ecf-41b2-8556-fc921347cbec · outbound

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ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-05T04:36:33.190064Z

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ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Unresolved cited work

Reference 82

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Observation 7a9f951a-e0bb-4775-8139-89ac60c957ff · outbound

This paper cites an unresolved cited work.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-05T04:36:33.174748Z

Source-reported events for the cited work

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Observation 7eb0a9ad-f87c-46d1-9f86-dc8ac93b7ecd · outbound

This paper cites Nowadays, most models typically incorporate a simple RevIN (Reversible Instance Normalization) module to ensure a basic performance lower bound.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Nowadays, most models typically incorporate a simple RevIN (Reversible Instance Normalization) module to ensure a basic performance lower bound

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.166894Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af4de299-616b-4f2a-a8e0-9fd8487d2aa4 · outbound

This paper cites All experiments are conducted on a single NVIDIA GeForce RTX 4090 GPU, with an Intel(R) Xeon(R) Gold 6338 CPU @ 2.00GHz, and each forecasting experiment is limited to 4 threads.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting All experiments are conducted on a single NVIDIA GeForce RTX 4090 GPU, with an Intel(R) Xeon(R) Gold 6338 CPU @ 2.00GHz, and each forecasting experiment is limited to 4 threads

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.158969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d0008c61-bd5f-4851-8012-a17e151519ca · outbound

This paper cites an unresolved cited work.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-05T04:36:33.151095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7f460bb1-c0a8-41d8-acb9-e8b88dbe7db9 · outbound

This paper cites With reference to existing work, we exclude Entropy and Lumpiness [28] due to manual sliding window, Shifting and Transition [7] because of the poorer math interpretability.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting With reference to existing work, we exclude Entropy and Lumpiness [28] due to manual sliding window, Shifting and Transition [7] because of the poorer math interpretability

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.143135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 67e126f8-37e5-459a-9425-b17bd2511555 · outbound

This paper cites We conduct systematic tests and observe that mean and amplitude variations do not affect property evaluations.

ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting We conduct systematic tests and observe that mean and amplitude variations do not affect property evaluations

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T04:36:33.135170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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