Paper Citation Record · LEDGER

DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2306.01984.

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

pith.paper-citation-record.v1
2306.01984 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:39:01.540715Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

21
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 49fa83e7-9037-41bc-a2df-9499635029d0 · inbound

Advancing Marine Heatwave Forecasts: An Integrated Deep Learning Approach cites this paper.

Advancing Marine Heatwave Forecasts: An Integrated Deep Learning Approach DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T17:48:53.335898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 575458f3-df8c-4668-90cf-e46ad8242239 · inbound

Alternators With Noise Models cites this paper.

Alternators With Noise Models DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:39:01.540715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58ccd5c4-cb7b-4926-8a94-48973c606e57 · inbound

Flow marching for a generative PDE foundation model cites this paper.

Flow marching for a generative PDE foundation model DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T13:51:25.463439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ede300c6-6e3d-45af-8769-67506bf9d2c9 · inbound

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems cites this paper.

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 292

Resolution: verified exact; arxiv_id, observed 2026-05-20T08:03:08.824728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 067cd9db-fb4b-4569-8a9b-4a181a1c4cbe · inbound

DiffUNet^2: Bidirectional Prediction, Probabilistic Generation and Collaborative Visual Discovery for Scientific Data cites this paper.

DiffUNet^2: Bidirectional Prediction, Probabilistic Generation and Collaborative Visual Discovery for Scientific Data DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-28T08:11:49.476921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dd63b3b9-2f08-4238-9cd6-2d0bdf46bfce · inbound

Learning Climate Variability from Scarce Data with Diffusion Models: A Test Case for ENSO cites this paper.

Learning Climate Variability from Scarce Data with Diffusion Models: A Test Case for ENSO DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T01:58:53.781911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5ad90c43-ce95-4a93-a834-fbc9961fdf97 · inbound

Spectral Diffusion for Protein Dynamics cites this paper.

Spectral Diffusion for Protein Dynamics DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-11T21:27:22.768274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.