Paper Citation Record · LEDGER

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2509.02341.

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

pith.paper-citation-record.v1
2509.02341 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:40:49.066120Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T06:33:31.828576Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T06:35:29.658041Z

Reference resolution

46 of 46 outbound references displayed

verified exact4
verified fuzzy23
unresolved19
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 17987dc5-6633-4535-bbf1-dadd8d234935 · outbound

This paper cites Financial time series forecasting with deep learning : A systematic literature review: 2005–2019.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Financial time series forecasting with deep learning : A systematic literature review: 2005–2019

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.878601Z

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

Observation 940ac012-7832-4647-bb51-d48c3f59b5dc · outbound

This paper cites Liu Sheng, and Joseph Dunbar.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Liu Sheng, and Joseph Dunbar

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.865405Z

Source-reported events for the cited work

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Observation 45575b9f-3490-4565-b966-ea315725d2f4 · outbound

This paper cites A review of time-series forecasting algorithms for industrial manufacturing systems.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting A review of time-series forecasting algorithms for industrial manufacturing systems

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.853600Z

Source-reported events for the cited work

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Observation 6e7d81ed-17f1-4a4f-9969-db622c61da29 · outbound

This paper cites Studies on time series applications in environmental sciences.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Studies on time series applications in environmental sciences

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.840779Z

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Observation 1c5b60a4-2f9d-4a88-9363-d0d75ef4f1d4 · outbound

This paper cites Review of time series traffic forecasting methods.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Review of time series traffic forecasting methods

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.828587Z

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 fc51b565-3259-47df-bb4b-54235f97b3e4 · outbound

This paper cites Forecasting e-commerce consumer returns: a systematic literature review.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Forecasting e-commerce consumer returns: a systematic literature review

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.816468Z

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 3a5cdb35-e124-4614-8686-d8fc3b955c47 · outbound

This paper cites Time Series Analysis for Education: Methods, Applications, and Future Directions.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Time Series Analysis for Education: Methods, Applications, and Future Directions

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:40:49.550277Z

Source-reported events for the cited work

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Observation 58021fc8-3551-4a8f-947a-13c77c1f0559 · outbound

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

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting A Survey of Deep Learning and Foundation Models for Time Series Forecasting

Reference 8

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Source-reported events for the cited work

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Observation c4948b1f-4b0e-4d37-a1f6-b9a581fbd5dd · outbound

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

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Time-series forecasting with deep learning: a survey

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.801813Z

Source-reported events for the cited work

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Observation 22a974a1-9907-48a6-b3a2-bbdc2a290ed8 · outbound

This paper cites Torres, Dalil Hadjout, Abderrazak Sebaa, Francisco Martínez-Álvarez, and Alicia Troncoso.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Torres, Dalil Hadjout, Abderrazak Sebaa, Francisco Martínez-Álvarez, and Alicia Troncoso

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.789232Z

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 ec256b74-f3c3-4be4-88c3-1ea8e136fdc2 · outbound

This paper cites Probabilistic forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Probabilistic forecasting

Reference 11

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Source-reported events for the cited work

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Observation cf372633-3a20-418d-b8b3-d007da7235a0 · outbound

This paper cites Bazionis and Pavlos S.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Bazionis and Pavlos S

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.764505Z

Source-reported events for the cited work

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Observation fd79e53c-352b-4d71-a917-4224cb1be6bb · outbound

This paper cites A review of predictive uncertainty estimation with machine learning.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting A review of predictive uncertainty estimation with machine learning

Reference 13

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Observation 8a563570-72d4-4d9b-afa1-451c05e17b59 · outbound

This paper cites Diffusion models for time-series applications: a survey.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Diffusion models for time-series applications: a survey

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.751199Z

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 2c774935-160c-4c78-9aba-7a8c4f8f4795 · outbound

This paper cites Predict, refine, synthesize: Self-guiding diffusion models for probabilistic time series forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Predict, refine, synthesize: Self-guiding diffusion models for probabilistic time series forecasting

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.738408Z

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 0f0e7fe2-97bf-412b-8b56-ae46401d110a · outbound

This paper cites The Rise of Diffusion Models in Time-Series Forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting The Rise of Diffusion Models in Time-Series Forecasting

Reference 16

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Source-reported events for the cited work

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Observation bed2a4a9-546c-4a15-a150-ec3fd6499803 · outbound

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

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 17

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Observation cb98d25e-d6dc-4c9e-b560-dd7ff43cea98 · outbound

This paper cites Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

Reference 18

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Observation c6b6dcd3-955e-4838-a04e-981d5aeeccdb · outbound

This paper cites An Analysis of Linear Time Series Forecasting Models.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting An Analysis of Linear Time Series Forecasting Models

Reference 19

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Observation 07b720fb-c2bd-45bf-af3e-2029775d0a67 · outbound

This paper cites Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows

Reference 20

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Observation 855fb998-e75e-4377-a800-70296ce8bad2 · outbound

This paper cites Is mamba effective for time series forecasting? Neurocomputing, 619:129178, 2025.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Is mamba effective for time series forecasting? Neurocomputing, 619:129178, 2025

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.726292Z

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 b1153022-45b3-46e9-bbe3-6c7f26e614d5 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 22

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Source-reported events for the cited work

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Observation 41dd9277-13b4-4fd6-be76-524159a103d5 · outbound

This paper cites Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting

Reference 23

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Source-reported events for the cited work

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Observation b62bbdd3-4800-4bc5-84c4-32fad87ef318 · outbound

This paper cites Transformer-modulated diffusion models for probabilistic multivariate time series forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Transformer-modulated diffusion models for probabilistic multivariate time series forecasting

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.713612Z

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 3a18207d-be32-4231-9286-b1a63cf7e612 · outbound

This paper cites Diffusion-based decoupled deterministic and uncertain framework for probabilistic multivariate time series forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Diffusion-based decoupled deterministic and uncertain framework for probabilistic multivariate time series forecasting

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.701014Z

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 73f2fb50-b24f-4863-a853-90b749119ecc · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 26

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Observation 406d37cc-e54e-4dc4-a364-9bf8a14082b4 · outbound

This paper cites MVG-CRPS: A Robust Loss Function for Multivariate Probabilistic Forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting MVG-CRPS: A Robust Loss Function for Multivariate Probabilistic Forecasting

Reference 27

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Source-reported events for the cited work

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Observation 4bcfe03c-131f-49ac-a56e-b4255dbb47dc · outbound

This paper cites Denoising Diffusion Implicit Models.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Denoising Diffusion Implicit Models

Reference 28

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Observation 81f67489-8e3c-4368-b7f2-8e4cf53aedf0 · outbound

This paper cites Denoising diffusion probabilistic models.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Denoising diffusion probabilistic models

Reference 29

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Observation 88135990-77b0-4a34-b4df-e55904677e0d · outbound

This paper cites StatProof- Book/StatProofBook.github.io: StatProofBook 2024, 2025.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting StatProof- Book/StatProofBook.github.io: StatProofBook 2024, 2025

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.671199Z

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

Observation 419baf46-7848-4e46-87a3-e4703139da8d · outbound

This paper cites Matheson and Robert L.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Matheson and Robert L

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.657180Z

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 e52c3aba-a2f8-4c6c-850d-eafc1ec9f20a · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.644376Z

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Observation a26576bd-69ab-4312-843e-45a61eec469b · outbound

This paper cites Accurate uncertainties for deep learning using calibrated regression.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Accurate uncertainties for deep learning using calibrated regression

Reference 33

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Observation 6ac76622-8516-4b8e-98d4-94714c93da02 · outbound

This paper cites Nominality score conditioned time series anomaly detection by point/sequential reconstruction.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Nominality score conditioned time series anomaly detection by point/sequential reconstruction

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.618454Z

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Observation 8cc07396-b3ec-4a00-a38f-310351794b85 · outbound

This paper cites Conformal prediction with temporal quantile adjustments.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Conformal prediction with temporal quantile adjustments

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.605245Z

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Observation 873a4da9-0b89-421c-8d46-43897a935d98 · outbound

This paper cites Conformalized quantile regression.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Conformalized quantile regression

Reference 36

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Observation eacfd9e2-a44e-49d8-9c8c-bbd0f1ad53d9 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Gaussian Error Linear Units (GELUs)

Reference 37

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Source-reported events for the cited work

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Observation 4d9e67a9-a0a7-416a-bc25-7d1604262809 · outbound

This paper cites Modeling long-and short-term temporal patterns with deep neural networks.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Modeling long-and short-term temporal patterns with deep neural networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.584072Z

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 c59010f7-6d65-436d-beba-744e9db61f7f · outbound

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

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 39

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Source-reported events for the cited work

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Observation bccc72be-5b88-4000-a8da-9eb8649ef72c · outbound

This paper cites Non-autoregressive conditional diffusion models for time series prediction.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Non-autoregressive conditional diffusion models for time series prediction

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:40:49.563026Z

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 4fabfa48-e158-45fb-9c69-702a484200f0 · outbound

This paper cites TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting

Reference 41

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Observation 20db3d57-fe77-4969-a2e6-84babf5c9a4c · outbound

This paper cites Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models

Reference 42

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Source-reported events for the cited work

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Observation 72534435-608b-4648-ac02-9a9ab43891df · outbound

This paper cites TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T11:40:49.053894Z

Source-reported events for the cited work

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Observation f6ee0910-ac80-4924-b97a-00d8987def0b · outbound

This paper cites Chronos: Learning the Language of Time Series.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Chronos: Learning the Language of Time Series

Reference 44

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Source-reported events for the cited work

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Observation 69b82c7b-67b4-4733-8ef9-3563820a749f · outbound

This paper cites Difusco: Graph-based diffusion solvers for combinatorial optimization.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Difusco: Graph-based diffusion solvers for combinatorial optimization

Reference 45

Resolution: verified exact; raw_fallback, observed 2026-08-05T11:40:49.317818Z

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Observation 6cd1a67d-22a1-49b4-9e83-1c7ddb5a3e7f · outbound

This paper cites an unresolved cited work.

RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting Unresolved cited work

Reference 46

Resolution: verified exact; raw_fallback, observed 2026-08-05T11:40:49.230052Z

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

Observation 17c75de0-5dc6-453e-a46e-f04cdb65c1fc · inbound

Mind the Residual Gap: Probabilistic Downscaling under Real-World Bias cites this paper.

Mind the Residual Gap: Probabilistic Downscaling under Real-World Bias RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:35:29.660019Z

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.