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Paper Citation Record · LEDGER

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2508.18565.

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

pith.paper-citation-record.v1
2508.18565 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:01:25.988625Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

  • verified exact4
  • verified fuzzy18
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bb9236f5-7d90-44fb-90ad-5c2675cf6b9e · outbound

This paper cites Tabatabaei, R.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Tabatabaei, R

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2b60b483-b1dc-456f-9518-217e46f3e2a5 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 2

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5d2e2f8e-00db-4016-b83f-1f13421669fc · outbound

This paper cites Casulli, Semi-implicit finite difference methods for the two-dimensional shallow water equations, Journal of Computational Physics 86 (1990) 56–74.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Casulli, Semi-implicit finite difference methods for the two-dimensional shallow water equations, Journal of Computational Physics 86 (1990) 56–74

Reference 3

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b646730e-0214-4444-98e8-3feaecbd1be7 · outbound

This paper cites Kurganov, D.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Kurganov, D

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation daef57e0-acbf-4349-b79b-1f68b1826428 · outbound

This paper cites Alcrudo, P.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Alcrudo, P

Reference 5

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1973b509-fb24-497a-b5e2-0ae0d7aeb52f · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9a8eb4f8-5521-4a0f-974f-ba6f24852e54 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6fcc235c-cf16-4f44-952d-46f5bfae8aae · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cbae4fe4-053f-439e-b742-086f2ebd3259 · outbound

This paper cites Babanezhad, A.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Babanezhad, A

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5b097805-f843-4a28-b6e6-06aeef315a8e · outbound

This paper cites Lagha, G.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Lagha, G

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 997d5477-a4f0-4a32-bd9b-dd0b58d4210a · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 15ad836f-5622-4cd6-8eae-4fd6f8252222 · outbound

This paper cites Fresca, A.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Fresca, A

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5963305a-162d-4d0c-9428-051a87789da8 · outbound

This paper cites Drakoulas, T.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Drakoulas, T

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8a9ecc01-f842-463e-8ae3-6fe9301a39d8 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 14

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 651190f9-00a4-44e6-9b7d-1f571e134750 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 15

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2aafee51-dbec-407a-ac4e-922efdd011f4 · outbound

This paper cites Dateformer: Time-modeling Transformer for Longer-term Series Forecasting.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Dateformer: Time-modeling Transformer for Longer-term Series Forecasting

Reference 16

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation eeab0989-792d-45a8-b6b2-dbb1cd9b4a6c · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5cff4adf-53c1-4cc0-bbca-ccaf967e0b8d · outbound

This paper cites Multi-Step Embed to Control: A Novel Deep Learning-based Approach for Surrogate Modelling in Reservoir Simulation.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Multi-Step Embed to Control: A Novel Deep Learning-based Approach for Surrogate Modelling in Reservoir Simulation

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d7ca2409-bda4-4fa7-981c-fbdcdaf621ca · outbound

This paper cites Trehan, K.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Trehan, K

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 58b73e0b-e4b9-424f-a3ea-04b100541e8a · outbound

This paper cites Cheng, Y.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Cheng, Y

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 560212eb-d552-44ff-b470-47f1eb89a6c5 · outbound

This paper cites Fukami, K.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Fukami, K

Reference 21

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 62f5859c-ebac-4080-95d6-c0c229a0fbf2 · outbound

This paper cites Hasegawa, K.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Hasegawa, K

Reference 22

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3535a6d3-bfab-459f-976b-747d2db27a74 · outbound

This paper cites Maulik, B.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Maulik, B

Reference 23

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 32011b88-4e8c-4901-bbc6-bd1505c392e6 · outbound

This paper cites Raissi, P.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Raissi, P

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 97c00a88-a374-4c31-98d9-9142adbbd29c · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cdf05e30-c520-4d48-a461-43ce5ca50589 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 26

Resolution
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Source-reported events for the cited work

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Observation 4d400872-f95e-41b2-b0a7-1ad73e1491db · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fb55cbbb-fcdc-4096-aade-37f8eb20e324 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0e1b952b-0102-4bdf-bc8b-8e23012dca7b · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 29

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 398b6b78-425d-4c93-9de3-b85a99e6f1ab · outbound

This paper cites Raissi, Deep hidden physics models: Deep learning of nonlinear partial differential equa- tions, Journal of Machine Learning Research 19 (2018) 1–24.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Raissi, Deep hidden physics models: Deep learning of nonlinear partial differential equa- tions, Journal of Machine Learning Research 19 (2018) 1–24

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7c2bf453-a83a-4357-9b3e-dc838b7f9c05 · outbound

This paper cites De Bézenac, A.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics De Bézenac, A

Reference 31

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fb5bc48f-0c0d-415c-930f-107457842f3b · outbound

This paper cites Chattopadhyay, P.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Chattopadhyay, P

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cc5f651f-486d-4f61-8328-5122dc9a3c4f · outbound

This paper cites Bielitz, D.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Bielitz, D

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9e16ffd6-0e11-4bd0-9ed7-f5837ed5a507 · outbound

This paper cites Learning from Predictions: Fusing Training and Autoregressive Inference for Long-Term Spatiotemporal Forecasts.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Learning from Predictions: Fusing Training and Autoregressive Inference for Long-Term Spatiotemporal Forecasts

Reference 34

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4f834928-04ce-4749-8f2c-8e32652b59cd · outbound

This paper cites Learning Controllable Adaptive Simulation for Multi-resolution Physics.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Learning Controllable Adaptive Simulation for Multi-resolution Physics

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-15T17:01:26.038522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9a940591-8170-4dc7-8d85-70f380e30242 · outbound

This paper cites Message Passing Neural PDE Solvers.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Message Passing Neural PDE Solvers

Reference 36

Resolution
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no resolver link, observed 2026-08-15T17:01:25.959624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ac069253-4eb4-4b93-805e-e89d005834e1 · outbound

This paper cites Cheng, M.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Cheng, M

Reference 37

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1815e502-5ec4-43a7-a8d5-8b43e2c618b2 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 38

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation bfd503db-b421-47d1-a5ac-12b44804ff62 · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 39

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3bb2c613-4c21-480a-a858-e57f9ce32d3f · outbound

This paper cites Graves, A.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Graves, A

Reference 40

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e9f0d68e-2783-4a8d-8220-7cc0eddbf4fd · outbound

This paper cites Vaswani, Attention is all you need, Advances in Neural Information Processing Systems (2017).

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Vaswani, Attention is all you need, Advances in Neural Information Processing Systems (2017)

Reference 41

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8f04f07c-46f3-4e37-94fe-e96eefb510ca · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 42

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6a1c57f7-c328-4ba0-a306-5960b9ede4fb · outbound

This paper cites an unresolved cited work.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Unresolved cited work

Reference 43

Resolution
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 25e74a5a-8c03-4906-a1de-a614ac6fddbf · outbound

This paper cites On the difficulty of training Recurrent Neural Networks.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics On the difficulty of training Recurrent Neural Networks

Reference 44

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0ef6004-22ed-488f-a61f-f9693b9def22 · outbound

This paper cites Hochreiter, J.

Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Hochreiter, J

Reference 45

Resolution
verified fuzzy
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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.