Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:21:08.711153Z
Paper Citation Record · LEDGER
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting
As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2506.05597.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
46 of 46 outbound references displayed
- verified exact0
- verified fuzzy39
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a69adb54-692c-40fe-b5f5-60243d61cd9d · outbound
This paper cites an unresolved cited work.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:21:09.205373Z
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.
Observation 9d0ba520-d04c-4eb4-80e6-ff4648e6f092 · outbound
This paper cites Recurrent neural networks for multivariate time series with missing values.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Recurrent neural networks for multivariate time series with missing values
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.193781Z
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.
Observation d97e5daf-f306-408b-92b5-ef97cad7a46a · outbound
This paper cites The M4 Competition: 100,000 time series and 61 methods.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting The M4 Competition: 100,000 time series and 61 methods
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.182835Z
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.
Observation 85ac441e-0ae5-40eb-84f7-b5fce4ff6733 · outbound
This paper cites an unresolved cited work.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:21:09.172606Z
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.
Observation 0b801126-e4b9-421d-b548-9ef044714aa0 · outbound
This paper cites Efficient Estimation of Word Representations in Vector Space.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Efficient Estimation of Word Representations in Vector Space
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.162108Z
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.
Observation 8a6c4fb9-ed12-464d-b86b-6ac7fd03cc15 · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.International Conference on Learning Representations (ICLR), 2021.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.International Conference on Learning Representations (ICLR), 2021
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.152503Z
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.
Observation 2ef0566b-efe5-4c64-9a50-69f035bb5208 · outbound
This paper cites Are transformers effective for time series forecasting? AAAI Conference on Artificial Intelligence, 2023.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Are transformers effective for time series forecasting? AAAI Conference on Artificial Intelligence, 2023
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.141713Z
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.
Observation e43f6bf8-bf32-408f-849b-36b2fd3fea51 · outbound
This paper cites SAMformer: Unlocking the potential of transformers in time series forecasting with sharpness-aware minimization and channel-wise attention.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting SAMformer: Unlocking the potential of transformers in time series forecasting with sharpness-aware minimization and channel-wise attention
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.131173Z
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.
Observation c28548d4-3e89-4326-b335-f440112107a0 · outbound
This paper cites ST-ReP: Learning predictive representations efficiently for spatial- temporal forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting ST-ReP: Learning predictive representations efficiently for spatial- temporal forecasting
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.120249Z
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.
Observation 0990bd79-5411-48fc-954a-870bd1446212 · outbound
This paper cites Long-term forecasting with TiDE: Time-series dense encoder.Transactions on Machine Learning Research, 2023.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Long-term forecasting with TiDE: Time-series dense encoder.Transactions on Machine Learning Research, 2023
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.110544Z
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.
Observation b1c34790-f643-4223-887c-ab9a4ee4be14 · outbound
This paper cites Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.101423Z
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.
Observation 5b82b695-1f2f-4290-b49d-05520e761a55 · outbound
This paper cites Quantum Optimal Control of Nuclear Spin Qudecimals in $^{87}\text{Sr}$.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Quantum Optimal Control of Nuclear Spin Qudecimals in $^{87}\text{Sr}$
Reference 12
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T10:21:08.787393Z
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.
Observation ef41d799-8332-468c-ad25-703262e90527 · outbound
This paper cites ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.092221Z
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.
Observation fee1f950-3e8e-437e-b814-676d6e863e49 · outbound
This paper cites Arik, Tomas Pfister.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Arik, Tomas Pfister
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.082696Z
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.
Observation dc4c474d-406b-4138-ac29-cffd43b72bc2 · outbound
This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.073614Z
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.
Observation 94fb6e9b-a4ac-4e35-9cf6-8c6d93600999 · outbound
This paper cites FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.064518Z
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.
Observation 30016afe-2d4d-41e6-850d-a8d934eb7d01 · outbound
This paper cites Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multi- variate Time Series Forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multi- variate Time Series Forecasting
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.054730Z
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.
Observation 2eba1d1a-c06f-489d-aa4b-6fedb8f82638 · outbound
This paper cites STAEformer: Spatio-temporal adaptive embedding makes vanilla transformer SOTA for traffic forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting STAEformer: Spatio-temporal adaptive embedding makes vanilla transformer SOTA for traffic forecasting
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.044956Z
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.
Observation e8b85701-c861-4b5d-80ce-2a2f3b7e992c · outbound
This paper cites Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.036111Z
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.
Observation db6282c7-00e7-4f06-8b7a-11691fec2d94 · outbound
This paper cites CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement37th Conference on Neural Information Processing Systems, 2021.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement37th Conference on Neural Information Processing Systems, 2021
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.026846Z
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.
Observation aab78c87-21e5-4664-a4b1-b8f60d2fec85 · outbound
This paper cites Adversarial sparse trans- former for time series forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Adversarial sparse trans- former for time series forecasting
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.016937Z
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.
Observation c2ddcc28-842c-4777-86ce-aff9911bd43b · outbound
This paper cites Factorization machines.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Factorization machines
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:09.007782Z
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.
Observation dbc849ce-a04c-4720-9cde-1951af696004 · outbound
This paper cites Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.998616Z
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.
Observation 7af6627e-287c-4d2f-8645-c47d194a5357 · outbound
This paper cites Liu, Schahram Dustdar.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Liu, Schahram Dustdar
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.989632Z
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.
Observation 565aa27a-5ae5-48ed-abfb-b1651f62c96d · outbound
This paper cites TimesNet: Temporal 2D- variation modeling for general time series analysis.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting TimesNet: Temporal 2D- variation modeling for general time series analysis
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.980770Z
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.
Observation 8eb5d345-43f5-47da-bea1-744729d4f5ac · outbound
This paper cites DeformTime: Capturing variable dependencies with deformable attention for time series forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting DeformTime: Capturing variable dependencies with deformable attention for time series forecasting
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.971174Z
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.
Observation 3e04aac1-aacc-44e9-bf43-df527b38d37f · outbound
This paper cites Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:21:08.568202Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 804907e6-96d3-49b1-8728-a6b1ddfd0ec3 · outbound
This paper cites Linformer: Self-Attention with Linear Complexity.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Linformer: Self-Attention with Linear Complexity
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:21:08.644737Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d850b65d-6f6d-4e3d-83c8-70d30769f047 · outbound
This paper cites Rethinking attention with performers.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Rethinking attention with performers
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.961073Z
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.
Observation fbbaecba-9713-4a86-bbfa-ad9084d296f2 · outbound
This paper cites Flowformer: Linearizing transformers with conservation flows.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Flowformer: Linearizing transformers with conservation flows
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.951409Z
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.
Observation 39a34d29-4833-4f3b-ad44-078a73959df4 · outbound
This paper cites DeepFM: A factorization-machine based neural network for CTR prediction.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting DeepFM: A factorization-machine based neural network for CTR prediction
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.942350Z
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.
Observation 8cbfd822-334c-4f32-82a9-8252d7797164 · outbound
This paper cites xDeepFM: Combining explicit and implicit feature interactions for recommender systems.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting xDeepFM: Combining explicit and implicit feature interactions for recommender systems
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.933037Z
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.
Observation 8c95ccab-d0cc-4cc8-834a-06549fd1b52a · outbound
This paper cites Attentional factorization machines: Learning the weight of feature interactions via attention networks.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Attentional factorization machines: Learning the weight of feature interactions via attention networks
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.923543Z
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.
Observation 5b69f229-9172-4b26-b5ba-bb1a23a6cf84 · outbound
This paper cites Deep & cross network for ad click predictions.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Deep & cross network for ad click predictions
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.914314Z
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.
Observation 7947b3bb-b289-4f1c-9714-c8cafb4d1aba · outbound
This paper cites Reversible Instance Normalization for Accurate Time-Series Forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Reversible Instance Normalization for Accurate Time-Series Forecasting
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.905326Z
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.
Observation 896f405d-46a2-42c0-b8d1-fc60cd9c6d19 · outbound
This paper cites Gomez, Lukasz Kaiser, Illia Polosukhin.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Gomez, Lukasz Kaiser, Illia Polosukhin
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.896010Z
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.
Observation f1a95bc6-451f-4421-8c70-697b70fd5c59 · outbound
This paper cites CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.886311Z
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.
Observation dac9e2c9-7850-42f6-8368-436b7dc08d01 · outbound
This paper cites Moment: A family of open time-series foundation models.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Moment: A family of open time-series foundation models
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.875652Z
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.
Observation c03e5c5a-5204-4ce7-a342-665293203211 · outbound
This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:21:08.685820Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fd55145-38be-49af-94b0-64e7fc63bd8a · outbound
This paper cites Thomas and Thomas M.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Thomas and Thomas M
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.865760Z
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.
Observation a14a2373-5d89-4b0c-b541-c2730826fd4d · outbound
This paper cites Forecasting: Principles and Practice.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Forecasting: Principles and Practice
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.856103Z
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.
Observation 7e48353c-30d3-4018-9e06-ef9637fd499e · outbound
This paper cites an unresolved cited work.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T10:21:08.845406Z
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.
Observation 021bfae2-37c6-46e8-8bcf-9f2348e0c1b7 · outbound
This paper cites Hanssens , Leonard J.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting Hanssens , Leonard J
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.833135Z
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.
Observation cd7b778d-ab2b-440e-9189-8f7608ee0753 · outbound
This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting,International Conference on Learning Representations (ICLR), 2024.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting,International Conference on Learning Representations (ICLR), 2024
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.821355Z
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.
Observation 629e8921-d1fb-4886-8a8c-5adc27bebaa1 · outbound
This paper cites SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction, 36th Conference on Neural Information Processing Systems, 2022.
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction, 36th Conference on Neural Information Processing Systems, 2022
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.809859Z
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.
Observation 25fe7006-70a2-4805-9b26-99567c143677 · outbound
This paper cites The PEMS dataset consists of traffic data in California that was introduced in [45].
FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting The PEMS dataset consists of traffic data in California that was introduced in [45]
Reference 2016
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T10:21:08.799147Z
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.
Pith citing papers
No inbound Pith citation observations are available.