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Paper Citation Record · LEDGER

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

As of 22 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

Typed states for the displayed outbound observations.

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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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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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Observation dcd841b0-6f7b-463b-931f-d557b55ef166 · outbound

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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This paper cites and Newman, M.

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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Observation f1aba4d7-673a-4001-807f-11dbe90ecc42 · outbound

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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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

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

Reference 13

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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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This paper cites and Petr\'oczi, A.

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

Reference 28

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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:b2e30212607cebafbf69538517299834dc6da4b289f70dcefc6347e980174a52

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=sha256:9c925efe15cbe365317d861f42f674fb06fefc887bc598be27c871d83d3d84a8

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=sha256:557a72d6237ad1716993a82c7b715b4172409583007641a23cf86327bea0f63d

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=sha256:004cf190aac8bd976cf1da57762996a4f8a6567cc0bbc3ba96cf276d5615ec31

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=sha256:26a90a19fe2f3f52c98adde7c59cdbfa082dc3e8c9dfefc129820c08e4d66efb

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:b8f6514f3408f4970ba765639ffe3e5af8862ecdfc0f1d51db2b463c1954fedc

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=sha256:8ee61cb2597080e0802bcfcd932d33446071ddd53abbe0157d078a889e208eb3

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.502883Z digest=sha256:3f920acef3b0271213f93c014a28634e71f5724645c31f944abcfe17f56742e8

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.506572Z digest=sha256:b6ff7cfc2842a3c40be528e8bb45e316d91d48aab15c1b83dd4c5fde58aa0c5f

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.510787Z digest=sha256:bb4e20ab44519429778721b3d2ca28cd7423a3bf7b51e0fb79ea1f04ec51cd0c

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.513918Z digest=sha256:43a8787a03497734d0e744b1c66fc2e2734f2413e69a05d6b9940a011c6bd317

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.517236Z digest=sha256:dbc58a1ea85e43c8792b3ad9861ad5a18b34ea595b94c1a14c8b0ff2da37cbf2

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.520816Z digest=sha256:abd6b9080b4e7d9d3a999d9dd28d9fc9356613bcbe898209c9c343c0addd87f6

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:abd3879186c841e8a7837b95e2b5e83807471ea77d9f47f54f56ca57fed26de1

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.528692Z digest=sha256:bac14aa5d34128a90764ef8d13530901b801bd87a8e910d363a837b82c05e5ea

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:f5fe2975e55b2ad89bfc155283cd9cf6ae142b91bd1e526c75435995259636e2

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.537508Z digest=sha256:6c8b13dd5b838bc24068548ceb809fadb356283a12dfd7dca905521435f4c347

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=sha256:1aadb80bae8e3079312bfcf984cc8c8cd5f2b04185acd111492913ca6a0c9dc3

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.546158Z digest=sha256:3cba971d25bee6637786145dde2d2558d3c2be83e930ca7a12843b7d3bf8fc4c

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.549823Z digest=sha256:fd06e240d13a0295491474c5903e213e424eec52d0d729e7a0469ab251ac54ca

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.553491Z digest=sha256:554c757a94e8cc08be560aa42e23fe5d7e0ceb83a8edecc00f1799e7b84abb53

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.557177Z digest=sha256:ff9a41b73c41de4daa700c828ffd6bf7224ade95dfa0ae963b6963de3bfd0962

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.560803Z digest=sha256:6e904408dc46846c461063002ee36e0558dc9304bd74f3d1966f3d13c07f1ba7

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.564410Z digest=sha256:190210447e71102954bf5075d688928413ba54a1cb1df498e01d29ea76068528

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.569231Z digest=sha256:33ea1df8f21f0ce0e141dea2b18d46bcceca6c34a62cc5f922a13948aa513365

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.573063Z digest=sha256:e185304bc247d3755774fef029580c5371a1871f2856f60f0bd65807d48e9100

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=sha256:726c8c6e6c028a1bb08885878d86752ca6319de90085643610ca72d468a984b6

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=sha256:082ee1d65e5d51c4b55e0b7d648bf50b7a0260b1dcd537c4aa49b7258c236a53

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.584217Z digest=sha256:9e31f2b504a543b56d00334799d7817c4b0442b986112cc166a499d2ed09d06f

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.588155Z digest=sha256:084b42142e5617e10cf14aaa6af6878e5b7dea93172aa56b49be6a7ae501494b

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.592129Z digest=sha256:d131a9216fe06d552918ea45e5566d1817c3b8715d38e7977b39be590b6e7479

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.595568Z digest=sha256:0329b3a49585ff212b7e14d5933c1be8e00afa3ebc5ba0d5a4d1f7ef2abbd8e9

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.599609Z digest=sha256:047a5dd3c3c65f9f58ae0f7827fbf1fe7b60a0dbc89694fc42d4ddf3d04b8bc3

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.603272Z digest=sha256:b1c9f16bde861795bdf81a7492a70afcbf3b022a740ab66029a8e2c56ee2105a

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.607580Z digest=sha256:cb9477bab8077915be2d69e598dcf80fe9ab7d30aaacb6e968b94273998ab7de

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.612192Z digest=sha256:4cca71a6e0667a80eb66d8d1f449ab072a2b58e8646e8dddad6222034c688618

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.615887Z digest=sha256:3483ddbc75d282e71086c55751d1052e48c57332a310bec5b1450c6032d4d6c4

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.619840Z digest=sha256:719af91b809dbe5b922822ec01b4ec36b028e9f9dfa0d3afb202f3cb8d3ecc68

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.623487Z digest=sha256:8493a0e7ac62c25e9130f1be570eb0cde2d4a24a846f6f2de57cc93a47c99df1

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.626982Z digest=sha256:65afc31eb1f42e19c0f991ccae9335ac5c53b9aec1068b5f5d32648416b46286

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.630458Z digest=sha256:f6aa71f2e7975e2bb3d0688baf7202d37bed887cfee844dd7a3001dc20998e3d

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.633703Z digest=sha256:af36f792e268a9ec6b64437131579eb660e60c33d1e699830625fdf35c3b49d7

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.636801Z digest=sha256:526d2e7d7e4bb9cff2ef2704798c6692e4df26d8153fdc6e3b639b05be09e2a8

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.640011Z digest=sha256:8b9da75c2358cfa9b4bc4442813f5ae0a0707ea4ea6e241cfca06b7a40388a8e

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.643218Z digest=sha256:4f4cf2d6457d32100b46cca3a6cbad9e7332f96a3e8efcaaae2a433697974fac

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.646298Z digest=sha256:8428af20969ebb53bec49d81e693c3f16ef7b459d5718503da51705d0ef3292d

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=sha256:3d6457361a34f0ecc39718fed640cf64944aa251899cb92d698476578a40e14e

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.652296Z digest=sha256:6171d3ddca4062adffb7574c07b4ea5d3b951e4a91948341b726ea03c2d5e8c8

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.655620Z digest=sha256:515041b3823e6dc4b9be2192d361405f9308999b816ee2b4333ec19339e563a7

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=sha256:5ee870061251ce7cbef5b210238bfd103b7d8b777b0526b7ed0386103b9f40e7

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:a7b185a1ef9b9f279fbf47a66bcae7e47df3523f91e8522a2c6d9dd80c2fa836

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=sha256:44fdeda5c10b154ae428f8d4ff10be9160d3d6da074361b1feb36fd2e49a1c9b

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.669992Z digest=sha256:9a5b1e108564d3c1ce4b17d020fd884667a5b2595f590a3523c29b0339904996

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.673512Z digest=sha256:4428ca43cd5d5bc97471f2a625de9b65ffc955f94347ee034295434ebc1dc0f0

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.677379Z digest=sha256:24d6f1d154543763bcba2d5d61ad5cb1d4ad4c45bf30c234d92aa7aae9bee26c

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.681227Z digest=sha256:0a12299b84f669011c392eef2e50043057a2dae7431d9d1584124c4206fbd0cc

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.685087Z digest=sha256:ec22102d327e85b6a03ef4580991a1760d9b2a17ad204367f4e27b9a5b56fc40

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.688999Z digest=sha256:c703598385c8577a2e343dd0728d760814160eb80afd361a3f014d459ef7afea

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.692743Z digest=sha256:3ca8a77098f77ef0e5f1b34268fb4a6c4a260698692d69a6bd054245c275215a

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.696435Z digest=sha256:a674c3d250b5beebbf863ad2d1176a8ddf7f0ba43d9c2545755656af3bfafe72

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.700145Z digest=sha256:a1ccd89834d3212629c2736a67311b67b2dcb2b29b1933a10520d621029ba37c

Pith citing papers

No inbound Pith citation observations are available.