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Paper Citation Record · LEDGER

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

As of 14 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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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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Observation c443ea34-71b1-412a-b9c6-e8090268b09a · outbound

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

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

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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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Observation 07268887-79c1-4ac0-9324-9e771f68d084 · outbound

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:cfa05cf8749a42402e0a23a28d22c57f8e5d5874b1675a7445659063013e1c7e

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=sha256:7a9d0ac693e70e4ed2a2d05852c570b863e45f4da2060cb2b70fc711e322a28c

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=sha256:4c1851cc44b38eb8174e267da1a40c2ec9d8bd224edc26f008a21643eaa0a984

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=sha256:19b485d754f777dad083c53f601f46403572edad6acdd3d75e4d19e7f56e6820

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=sha256:3af271be0cb5da2aa59be799f0a70976fda777a3c76ea403bcb1e01adbd6a9d1

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:d7a45ccce86284d6563502a2b26f5a10b5646b1558f69c45f14197df01741735

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=sha256:42e54ea233098ba2e6a61fa814410007db75219e1c4f966a0b743e314920dcf3

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.502883Z digest=sha256:b6e448470a97ae687a92f6c3de336a7015468e432de9a40f7a44bf5632122494

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.506572Z digest=sha256:4f435ce4169ff9e3ceb2c03a53eefe32aefc6db2f36c5aefdf9e8486575664cf

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.510787Z digest=sha256:a75ce745619de0fb2015639e6940472ac3f2d6b0bd7af8c694f9e1f70ca6b18f

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.513918Z digest=sha256:8de7e6a98e2ec1bf9a055f39f5afbd215daa9e8d746c46a53ef4f3fc5656d30d

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.517236Z digest=sha256:7b5e997e2d675230f3bfed3f186b7b1a2645f19dbeebfa8adb9d1e3716afe290

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.520816Z digest=sha256:ee532cf8c026dcc4e7590c07035e899c66706511206a7bee279f015c84325308

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:f008e10af87c0fc4e7a477ea631571155f3b7bd5df60516e253a0c9d6bdfabca

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.528692Z digest=sha256:9d87a4228573703b9807642562574ca6e22f788ec62f19a6491a4a2422fe5f9a

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:d113a264adf1bb02764b816d5f61acd9183a49528c5816eca625994b1cccbd55

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.537508Z digest=sha256:9f99bb74d1cc206886a5b1d69a787c299ca49467bb881c5ae3e8fd2b342201f9

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:b04f167f5d6830eed9ecd09e3880db8fa925d6b18bf35726e4c60f8cb360faf0

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.546158Z digest=sha256:cef197c77a39b5a52ace0adc1103fe58d6dd226b6e02c391a280690c56713952

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.549823Z digest=sha256:5352530ca0bd3ba83fbb269f6787e575b6e287f95dd5c05be61efc01da56dade

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.553491Z digest=sha256:7a6cd19c0cc58852b3a7173b8527817246a95320a9bb487ea7d06e8466f8e5b0

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.557177Z digest=sha256:9ee7b546a104d65a272b253be63fd0d97a55339cd6a240e5746daa5b855b9595

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.560803Z digest=sha256:1fc869512118a9e20399da5897579a8e0951997b9268e0348ceb3febdc333fcf

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.564410Z digest=sha256:bfed8eac1ed7d141c7061a6cfaa764d79d9e5bb6d23e2fdaced2d019b3ea60d6

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.569231Z digest=sha256:54582b5ee618d848a775b4f423f0334c3347090aa91246c16f245d14b0dbcdf2

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.573063Z digest=sha256:7271f4121c9634a95562c666cea88776a46ce8c2b5a804da399b6f6d73e9bda2

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:b9911cabdc0a6be230205246f99b0d7c8b3a79eb64219b7bfe417ec3980d4b63

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=sha256:5853ddf0fd33a6138d258a2934b54097ed8fa24e236e1bd1207689780051c5ed

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.584217Z digest=sha256:d5af4f466a5c6b2c6dd31873f7916fb34a0838a1c83eb6aebc124e3db44ee15e

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.588155Z digest=sha256:0627cd120f14bbf0266f5c7d4e97a9cb4237c43a9ab1944988ad9b3e815901ff

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.592129Z digest=sha256:1a84e074cb9dd223ebce3aa26ca673e7a821d6b035622bd01a4b0f392bd253a6

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.595568Z digest=sha256:db7587fcd1eb60e627c54084d808e71ff5c48d0783e20b6db4b3a9dbf403fe11

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.599609Z digest=sha256:1ba18c7033c92d56c62cbbc684942c588548544ae77345cdd219f0946b0d84ad

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.603272Z digest=sha256:bb1c1c79e627a9a3d7eb90d7695b45913697273d1702703f65a40e0277dd8cb9

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.607580Z digest=sha256:498fca68f8ce394e907f24b53685910947eee6ecfe35426321603dbe24e3b2a0

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.612192Z digest=sha256:8b4c0d4b2bca5a1baa0581231117617d20d4a758b037f9e8ed62648f96d39e90

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.615887Z digest=sha256:1e43fd56f6530fcb063c7be5471694becc51c5d19bcc4564e9da2df417474491

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.619840Z digest=sha256:1a12bca70cc60a827cc36674a2feb0aa899078a7e39f67df8234d8a25311befc

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.623487Z digest=sha256:45a69c69367439bb79bbdfc14345f7208f780c8a036635d5c8b483825275433e

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.626982Z digest=sha256:9f8cba37de6c33e779b72f3e1dcd547e19da1c82e3b0c765f7fe27f97734ed55

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.630458Z digest=sha256:938b15e93d97cbc32008207bbfe51d3bc708d3cf239804a716f8ea3c73180cd6

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.633703Z digest=sha256:dfb5ab795f905fdb34945e154101152b72cef1aff0c712f051b0d83e2c1f73ec

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.636801Z digest=sha256:52d55e92419c4f30a5dcb81ce267bef42e00b1b79edb697dae72dfdb1f5b7ada

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.640011Z digest=sha256:063435bb8808e18d8263254dd2c6fa33dc53a44f0f3683f199142d471184c4ea

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.643218Z digest=sha256:75f560a5fecd88218a8beafe9b590730ba4d79fa6ac480ad8722644ce8f31a2a

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.646298Z digest=sha256:ab50113a58d2441fcc172d2087933f7b57bf65fac85f53547cafb4e476f1250a

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:e19aa4262152f4648e39136b9b5c2417d2e9aa05008ed66d94c52c5270215ffe

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.652296Z digest=sha256:e8d399455591a45df474cc5fef48055d465221adc4c42d3aaf05fe2cdb6f209a

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.655620Z digest=sha256:a62ea4913fd48cbfb548c3af85e3a8dd03f9042fbbd53149731e49a9951287b9

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=sha256:025c2da7c4b4417480f9f1a064d0664d01aa47999b37194e953351e9488e781c

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=sha256:86355370517dda940156f94f7f10d0bf4cd2a0dd830ac33cea93720c2b9692a0

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=sha256:9dd2fa116e2da4b3083acf6cc5cae0449e9990e13594385f1109a7e392d16e35

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.669992Z digest=sha256:a1d4acc4e4c3374f747d659602e9e5fffaaddaac43382448324a2913402b5c74

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.673512Z digest=sha256:c2ac96cfbee64ff175d7364c8786450a54bdc3036086293fa6b8edbb78d42781

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.677379Z digest=sha256:9d707018504235479c28b13604a8c912dd32d2d21a11aefc2a6278efbb1a1df9

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.681227Z digest=sha256:f910b6163b6a606cf68cf49dd440d759888575186a3b56e04d77a9b150f1c53f

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.685087Z digest=sha256:3b4069e4d2c1cde2c4c5f59b6ffdd81202dec0d4cd50a3887c70b4b0fe096cc4

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.688999Z digest=sha256:c8cc8c952c908b0207cc1f928561d22c0fbb4aaf59b58cc9bb86d628c145bd33

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.692743Z digest=sha256:12a22e29bbe7847dfcb8c7267230a8be5ec61e769ad504093a6e441849b7cd23

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.696435Z digest=sha256:d96c3694a2fb2b72ad1f4f0e259c517fd7467779a630161713eff5696aa8d5ea

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T00:31:24.700145Z digest=sha256:01468ace89225a1290b5d4616771324c5cf750d4a5c740d1393fb19a6c722d87

Pith citing papers

No inbound Pith citation observations are available.