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Paper Citation Record · LEDGER

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention

As of 12 August 2026, this Paper Citation Record lists 100 of 125 outbound references and 0 inbound Pith citation observations for arXiv:2608.07681.

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

pith.paper-citation-record.v1
2608.07681 v1

Coverage vector

measured 100 of 125 reference resolution

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measured 100 of 100 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 125 outbound references displayed

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External citation measurements

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Outbound references

Observation f175283a-874e-4eef-a12b-8fed158aad32 · outbound

This paper cites , title =.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention , title =

Reference 1

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Observation 46a3972b-af2d-435c-ac9f-3e496d7ec9de · outbound

This paper cites an unresolved cited work.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Unresolved cited work

Reference 2

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This paper cites and Reinhardt, T.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Reinhardt, T

Reference 3

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This paper cites and Albert, R.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Albert, R

Reference 4

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This paper cites 2011 , pages =.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 2011 , pages =

Reference 5

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This paper cites and Li, S.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Li, S

Reference 6

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Newman, M

Reference 7

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This paper cites an unresolved cited work.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Unresolved cited work

Reference 8

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This paper cites and Campari, R.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Campari, R

Reference 9

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This paper cites and Barthelemy, M.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Barthelemy, M

Reference 10

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 2011 , pages =

Reference 11

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Observation 49c46536-5caa-4a1b-94ee-95fe470f0b70 · outbound

This paper cites and Li, J.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Li, J

Reference 12

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Observation a3ad7cc8-954b-4162-b224-5eb76169c1b9 · outbound

This paper cites and Wang, X.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Wang, X

Reference 13

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This paper cites an unresolved cited work.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Unresolved cited work

Reference 14

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Wu, T

Reference 15

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Wang, R

Reference 16

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Petr\'oczi, A

Reference 17

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Liang, Z

Reference 18

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Gao, L

Reference 19

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Liu, D

Reference 20

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Roberts, S

Reference 21

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Yeung, D

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention , title =

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Unresolved cited work

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Unresolved cited work

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 2012 , pages =

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Fortunato, S

Reference 27

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Pellegrini, M

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Diaz-Guilera, A

Reference 29

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention , title =

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Fortunato, S

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention and Rifqi, M

Reference 32

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Machine Learning , volume=

Reference 33

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 2000 , publisher=

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Joint European conference on machine learning and knowledge discovery in databases , pages=

Reference 35

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Procedia CIRP , volume=

Reference 36

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Engineering Applications of Artificial Intelligence , volume=

Reference 37

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Galaxies , volume=

Reference 38

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PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Journal of Space Weather and Space Climate , volume=

Reference 39

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This paper cites Time Series Analysis: Data, Methods, and Applications , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Time Series Analysis: Data, Methods, and Applications , volume=

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.475993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.475993Z digest=sha256:a8ad6af338548ea0f321a1186589fdadb1efb0d9920fe6e71970ed43670a69dd

Observation 67e39eb2-1799-4a29-a3f0-843d3c376e92 · outbound

This paper cites Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pages=

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.479746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.479746Z digest=sha256:941952370a39593a58c5d36d8762022ebd265d819bf9b62db25ebc31c2dc295b

Observation 91a01b35-5e43-4ff7-8ee1-a7d03c809cfd · outbound

This paper cites Knowledge-Based Systems , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Knowledge-Based Systems , pages=

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.483365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.483365Z digest=sha256:355b334ae9d31baddad25e18ab8f6ccd45a251b9e35cdb445f0c794693c9e9b2

Observation 1bd495a4-57ef-43ff-806b-d5e5f4db7275 · outbound

This paper cites Journal of big Data , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Journal of big Data , volume=

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.487396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.487396Z digest=sha256:84e3f48584501c3dbdbb263e802217196f67435afac757aaba4c1f7f112ceea9

Observation 24b5c76f-9e8c-4856-b5c0-c55bb28aec41 · outbound

This paper cites 2019 International joint conference on neural networks (IJCNN) , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 2019 International joint conference on neural networks (IJCNN) , pages=

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.490958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.490958Z digest=sha256:a73768f15818405fac0110a44d7bb2945bb7da2b31c277083ccf17c88189753f

Observation 50ed9e48-ded7-4aa9-9be0-e7bf9a190b8f · outbound

This paper cites Measuring the tendency of CNNs to Learn Surface Statistical Regularities.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Measuring the tendency of CNNs to Learn Surface Statistical Regularities

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.494542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.494542Z digest=sha256:40e51f5f34dae741dd05a39c3a4e74e00598409ba494efdab0cb9e0d93cf4f59

Observation c3383784-b932-47db-824d-b50af5f2b93f · outbound

This paper cites Data mining and knowledge discovery , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Data mining and knowledge discovery , volume=

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.498838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.498838Z digest=sha256:dd83b63d7331faa15dafb593eeca77e90d423b644f33ca91aed4062eb59e651e

Observation 568abe07-722c-4ed1-aaa8-dd35e0d550e3 · outbound

This paper cites Structural Health Monitoring , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Structural Health Monitoring , volume=

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.940186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.502883Z digest=sha256:46e8861328de92286696565735ccd7e2d3cf5a760c169dbc546b8be69e28a76e

Observation 9c16f975-f91e-47e6-9454-783c0028a098 · outbound

This paper cites Journal of Intelligent Manufacturing , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Journal of Intelligent Manufacturing , volume=

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.929492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.506572Z digest=sha256:cb21165d80475377c8ce6065cdf122d1c19d1cd555d35a562bb6d2d6136c5d86

Observation 9455ec26-a02c-4467-88a3-4c1af5d3f383 · outbound

This paper cites ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.917496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.510787Z digest=sha256:d2d9dd899450f6da00115c983f2f658330cee04c35c8b7f6679e188cfa29650b

Observation 86b9a05a-ac5f-48d5-9113-ef79cca6799b · outbound

This paper cites Logic Journal of the IGPL , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Logic Journal of the IGPL , volume=

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.905343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.513918Z digest=sha256:1b48110afaa135d55f8b602122c963504ab3ae2c683c0218430e3eacea7b9af3

Observation 74eafc91-241a-4da4-bf63-78c8ab0d54fb · outbound

This paper cites IEEE access , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention IEEE access , volume=

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.893234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.517236Z digest=sha256:68f978a678e3f5e62af6f2d85f990be1e746ccb97e38af1843e4f320f34b0b4b

Observation 413e13dd-9a6a-407e-847c-dda013ff5722 · outbound

This paper cites 6th FIRST 2022 International Conference (FIRST-ESCSI-22) , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 6th FIRST 2022 International Conference (FIRST-ESCSI-22) , pages=

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.881693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.520816Z digest=sha256:eda506f51292d6b43b5b37a7fd278ada2fbf3afea7b172c068d8ad2d7ed4c2e9

Observation 7fa27446-d38b-4d27-9076-536a094845c6 · outbound

This paper cites Multi-Scale Convolutional Neural Networks for Time Series Classification.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Multi-Scale Convolutional Neural Networks for Time Series Classification

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.523975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.523975Z digest=sha256:bdce664343d1091a3f8bfec45298069b8abd2a6852e4aeb9032aacda7e289e6f

Observation 50aa3dcb-a7c1-4d32-a5a7-e2b588996af4 · outbound

This paper cites International Journal of Conceptions on Computing and Information Technology , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention International Journal of Conceptions on Computing and Information Technology , volume=

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.869954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.528692Z digest=sha256:929f62f828d08da54cb2e6b8d2eed95ee449f80d4c6da4cc409bdc2fa9adb496

Observation dfee1b84-d476-4f32-9c0e-59d8d28cf71f · outbound

This paper cites Decoupled Weight Decay Regularization.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Decoupled Weight Decay Regularization

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.532715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.532715Z digest=sha256:6c0234a11baf2eb3a6d1c3dfa76394e83edd4cbc70741130d7818d9acde7bfef

Observation 3fffadac-fc8e-4de9-804b-808d06f2c9ed · outbound

This paper cites Dual sparse training framework: inducing activation map sparsity via Transformed $\ell1$ regularization.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Dual sparse training framework: inducing activation map sparsity via Transformed $\ell1$ regularization

Reference 56

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T00:31:25.105012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.537508Z digest=sha256:31c5bc3b477b8f9c1b52262449b5a5c621342765787c955e8e079a05af030b5f

Observation a055d659-3323-4a92-8682-fc223cf72c41 · outbound

This paper cites Neurocomputing , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Neurocomputing , volume=

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.542492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.542492Z digest=sha256:09c74db30d77bd49fb8a7cdfdd2a8a0ca8e6e64a9e8fb5214b9a0e039d0c0ee3

Observation 7517e212-4789-428e-a9a5-6754dadd06a9 · outbound

This paper cites Frontiers in applied mathematics and statistics , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Frontiers in applied mathematics and statistics , volume=

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.850797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.546158Z digest=sha256:453bc7ba672405778cba9e6c004e3677a32a14d79030b37ef34732b31ac0edf0

Observation 702c2e1d-a9da-4457-b1d7-72a2e8f322eb · outbound

This paper cites , author=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention , author=

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.837944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.549823Z digest=sha256:acbd3794900b87034cd9e651fd53dcfb6265ae210fb3382c0e795f68ac8e9712

Observation 7ae1533e-f8ea-4c1f-a180-b7e3a20acaed · outbound

This paper cites Neural Computing and Applications , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Neural Computing and Applications , volume=

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.822844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.553491Z digest=sha256:16055c2399ff0cadcb571d8c2392b942cb60a7ccb9a41b4c24136b86a8f5b172

Observation 9a9864f7-83cb-4f9d-8783-1a57e2b89d4f · outbound

This paper cites Machine Learning , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Machine Learning , volume=

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.809915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.557177Z digest=sha256:f3d75f8b80d9c6e04b81bac298321cbad35f6245a7f789f8550a9762977488b8

Observation 830bade0-b85b-4e58-b968-5bf784150818 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.797769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.560803Z digest=sha256:bc9038f9cbf7ae699fb96394b02c1e1679077b605dd8998db67841ce4a1b2920

Observation d0803550-c55f-44e9-aa0c-4be5fb8bc38b · outbound

This paper cites an unresolved cited work.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Unresolved cited work

Reference 63

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:31:25.786256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.564410Z digest=sha256:7771bb539ae6b0309ecaa624f9b14b602ea67c7c464417a6a32c3c6915b2c367

Observation f310aab3-0b56-4747-88af-22d408b5fc05 · outbound

This paper cites arXiv preprint arXiv:2309.09045 , year=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention arXiv preprint arXiv:2309.09045 , year=

Reference 64

Resolution
verified exact
raw_fallback, observed 2026-08-11T00:31:25.088914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.569231Z digest=sha256:d4cb58037ff0ff5430fce06021714e584ff28588a6dd6ed3f8d10b04e8846989

Observation 36399456-bd0b-4970-a9dc-8ec62f7050c7 · outbound

This paper cites 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) , pages=

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.773129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.573063Z digest=sha256:e410ecbca2e388c9b8e2c4cc375f932381ce36c8295f7885192b6b320112f54b

Observation 35adb525-23d8-4e22-891c-b3d815fdb9c8 · outbound

This paper cites ACM Computing Surveys , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention ACM Computing Surveys , volume=

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.576594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.576594Z digest=sha256:3db072ab18bb6bc492fa669b1d2bfd2e769d76af60e05fb2684d69e29e5bf5fc

Observation 6143e9fb-3ba2-4319-b334-0428f0b11f02 · outbound

This paper cites Grad-CAM: Why did you say that?.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Grad-CAM: Why did you say that?

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.580343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.580343Z digest=sha256:d1acd3567fa584b401a08eaf3b62aa134dfd50ac7925cd27b4078a0a091829a5

Observation 88b6d972-83ee-4392-be6c-2f7e3ec6f7da · outbound

This paper cites , author=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention , author=

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.754075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.584217Z digest=sha256:26d7d61403b5969bde141d79f76b859e012c00828256963adba60c217a18cce4

Observation edad7a14-8e48-462f-9a0a-85d0fafe4ccf · outbound

This paper cites One Explanation Does Not Fit XIL.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention One Explanation Does Not Fit XIL

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T00:31:24.927117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.588155Z digest=sha256:5925a324c43582a0ca5841a321dc5812281cc1dc6c6429577a2823b08c51de3b

Observation cfb9f6d5-982d-4f5b-a7a5-cd2a2e075bc4 · outbound

This paper cites Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society , pages=

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.744136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.592129Z digest=sha256:792e58a2e012b6e4d93b507d1438af2c6324c9447eb305e9925cc3b4e7d71882

Observation 6c50bc3d-7831-4798-a56a-3922a587fea6 · outbound

This paper cites British Journal of Educational Technology , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention British Journal of Educational Technology , volume=

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.734383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.595568Z digest=sha256:2b0766b16ca5c3cea39c23251011e7c44f80294c855a784fccdd0c30ccbc20ac

Observation 23e91143-22e2-464c-bae7-22f9d20c2794 · outbound

This paper cites Journal of Manufacturing and Materials Processing , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Journal of Manufacturing and Materials Processing , volume=

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.723296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.599609Z digest=sha256:61f24658f5f2fc703c6d5dbf9afc874240dcb7de436a2f58b1d747e86ca2bf57

Observation bd8424c8-70ee-4cc2-ad26-f6009c85e6c2 · outbound

This paper cites The International Journal of Advanced Manufacturing Technology , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention The International Journal of Advanced Manufacturing Technology , volume=

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.710343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.603272Z digest=sha256:26942bb48e5b6197cae6c7ff2ca8e6add1206f23c921aa016621c44da2760d08

Observation ced232b7-9e58-4c2e-8173-cf0a5735b14b · outbound

This paper cites Procedia Cirp , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Procedia Cirp , volume=

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.699158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.607580Z digest=sha256:c23efac463156f2b4b94a79266160cca45554bf81f8f1618e3d7893bde9ad505

Observation de016a3f-0527-45eb-8c2d-ab7fb2175b60 · outbound

This paper cites Procedia CIRP , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Procedia CIRP , volume=

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.688378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.612192Z digest=sha256:e917ebcc3c7a7ddffab5ef4984bd876304bf4842fb84b5cacbec84d3a5312ef4

Observation 85c53199-68fb-4002-a7b1-c1b65a50b90a · outbound

This paper cites Advanced Engineering Informatics , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Advanced Engineering Informatics , volume=

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.675627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.615887Z digest=sha256:5c476e4727f35020b91e1db0467448d6fdf7ccc453ec4613ce593fa408685455

Observation 34d88d60-c101-4091-afd4-35f09c20e519 · outbound

This paper cites The Astrophysical Journal , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention The Astrophysical Journal , volume=

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.662366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.619840Z digest=sha256:7e9101bda18132874c6630ff15984a8903c0aa05607964cd0e5d57ee525265a4

Observation c839743d-2a6c-4048-9c46-0d147640398f · outbound

This paper cites Monthly Notices of the Royal Astronomical Society , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Monthly Notices of the Royal Astronomical Society , volume=

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.650650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.623487Z digest=sha256:27eb5df7f5372a3aff40d2ed61f956ec99164a9b86cd5c1b0fde1828f663bd31

Observation 04f4b9e2-9f27-4979-839b-09b3b05e53b0 · outbound

This paper cites Monthly Notices of the Royal Astronomical Society , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Monthly Notices of the Royal Astronomical Society , volume=

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.636825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.626982Z digest=sha256:66363f3834b28d046d9b14be6da42d52a174342428f0e23b968459dba810e797

Observation 61001194-f3e3-48d0-ac61-7d63bce836b8 · outbound

This paper cites Monthly Notices of the Royal Astronomical Society , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Monthly Notices of the Royal Astronomical Society , volume=

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.620503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.630458Z digest=sha256:7f6fb1291474850b2dbbca927d6c39c7fb4892b76f70a6e3147076865eb607a7

Observation ea9844b8-4752-4b0e-972e-ff1520d18a42 · outbound

This paper cites Pattern Recognition , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Pattern Recognition , volume=

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.599197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.633703Z digest=sha256:f32b36340c4eb5e77e20722c1f3418e53ee6a23e7f70f393f01192ee99a90304

Observation 85e9f481-7031-4f75-9d0b-a0a3557668f5 · outbound

This paper cites Trusted Artificial Intelligence in Manufacturing: A Review of the Emerging Wave of Ethical and Human Centric AI Technologies for Smart Production , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Trusted Artificial Intelligence in Manufacturing: A Review of the Emerging Wave of Ethical and Human Centric AI Technologies for Smart Production , pages=

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.582771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.636801Z digest=sha256:bc4f588d9738a56737a370243ec604c9569fe62a3d0081300ea30b0bff1b10bf

Observation f545eb92-9f0a-4e07-a285-4579afdc3d9c · outbound

This paper cites Journal of Industrial Information Integration , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Journal of Industrial Information Integration , volume=

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.569033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.640011Z digest=sha256:572a728b97ce899547ef7ad684c9d9695e994ca71d3a5982beb6431dc33887c5

Observation 4bda8ce7-7bab-4a9e-b14b-d3504fd94670 · outbound

This paper cites Advances in Mechanical Engineering , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Advances in Mechanical Engineering , volume=

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.555114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.643218Z digest=sha256:08517e970fa9ab404e693d0ebc4169ef1ea63660c01582e24c0470a7ef1b8448

Observation 224a95e3-7a74-4584-8ce1-43ee8475d307 · outbound

This paper cites Universe , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Universe , volume=

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.537727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.646298Z digest=sha256:05fc87b9ab31e6e850ec1a250b837ffe30bc683ca70428e60bd035b2ebf9009d

Observation 14b83b2a-af7c-48e5-96a6-2fb35ea6c2a6 · outbound

This paper cites The Astrophysical Journal , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention The Astrophysical Journal , volume=

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.649350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.649350Z digest=sha256:925bfb2f1f68bf6c7e09b8299a59d0d30fbfe7452a7e10230aa0e30d366f263e

Observation 60c4cbc8-5d4e-4741-8e43-6b106891259b · outbound

This paper cites The Astrophysical Journal Supplement Series , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention The Astrophysical Journal Supplement Series , volume=

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.509921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.652296Z digest=sha256:19dcd825ffb1d8871d31a7f02d7f22fa1e34ffb6ed793996d7b9bbea7d1f5112

Observation d2b6c5e0-a45b-44b3-986a-fd448f45e87f · outbound

This paper cites Engineering Applications of Artificial Intelligence , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Engineering Applications of Artificial Intelligence , volume=

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.496396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.655620Z digest=sha256:171b6722e20e18bf1052390ba643e029935c1859a344006f6eaa666ec3a32c2e

Observation c00d9e0c-00f0-4a0f-850c-2a79d233d50c · outbound

This paper cites Advances in neural information processing systems , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Advances in neural information processing systems , volume=

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.659115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.659115Z digest=sha256:088ec464aa691ff41a169f131916ae038c88d0490cd6044dc092f3d07012055f

Observation 956f8c3f-0066-4f4d-a500-afdaab4569ff · outbound

This paper cites Towards Transparent and Explainable Attention Models.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Towards Transparent and Explainable Attention Models

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.662612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.662612Z digest=sha256:7b94487e5743a49763be8c38493e3b46686c34823a6d604f08ab3cab7d65c5ef

Observation 585bfe6a-85bf-4304-bc47-771522fb9d37 · outbound

This paper cites Artificial Intelligence Review , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Artificial Intelligence Review , volume=

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-11T00:31:24.666431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:31:24.666431Z digest=sha256:3d601ee99b96b51f6e40fa0bc54bf66532ab5833723adb5908895d8c102a680e

Observation 82909430-a2e0-430e-8415-a4077680d26c · outbound

This paper cites Preprints.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Preprints

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.468516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.669992Z digest=sha256:4ffabd269717efa5c11f88f5627c575db759f676f8adf35701450ca5beaa0169

Observation 598d76d3-98e2-4ad5-a7aa-83489bbe6d3d · outbound

This paper cites Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure

Reference 93

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T00:31:24.900587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.673512Z digest=sha256:a8bdb6cf6e3cdc28a03e9d951edad2ba4f17757c1eb02ee77fb6167d9e30609a

Observation 199aa971-1334-4463-b03c-4437501b9f68 · outbound

This paper cites Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks

Reference 94

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T00:31:24.885286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.677379Z digest=sha256:48e19906ac33f200ea51aec020a8b59d70b5acf841308c362d70b49b1654c165

Observation 64527f71-935c-437a-8866-c7f7ba3d64ba · outbound

This paper cites Results in Engineering , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Results in Engineering , volume=

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.455514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.681227Z digest=sha256:5702029e4f299247acf5637ab5ef5499df45474d44a3510c85afef4c0a24f6d4

Observation a337b754-14c0-474b-9512-839a277df43c · outbound

This paper cites Energy , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Energy , volume=

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.436705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.685087Z digest=sha256:b2be57cff66e483171e6e3f61b83d846a8cb21a405fcef32cb42405e260fe4e4

Observation 05cf5a79-645c-444b-9eeb-5c4642254195 · outbound

This paper cites Energy , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Energy , pages=

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.423679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.688999Z digest=sha256:a6306cbf66f99f6ef44174451abe5642be75f90c7f1d14478838f4dd87361fe4

Observation b1a52d76-480d-4407-9891-98c06f4f7f37 · outbound

This paper cites Energy and Buildings , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Energy and Buildings , volume=

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.409380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.692743Z digest=sha256:2b605509a2551c10940e4ee2947e6f1d75b5cb4478e9b1f28f4b5782647fc696

Observation 00c1e797-55fd-49d2-8512-1e73ece0ce32 · outbound

This paper cites IEEE access , volume=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention IEEE access , volume=

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.397956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.696435Z digest=sha256:fa034bec89ecc9c0974179ba4c2a655b632e6bb84c4483ce9c21bb31c0d9d75b

Observation 4e16b1f1-4d20-443d-b90b-5cac44ac6d84 · outbound

This paper cites Joint European conference on machine learning and knowledge discovery in databases , pages=.

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention Joint European conference on machine learning and knowledge discovery in databases , pages=

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:31:25.386374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.700145Z digest=sha256:eb85e4565d29465a66cd7b1ae18a01d13361ead65cd320f7d7240a272b693155

Pith citing papers

No inbound Pith citation observations are available.