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Paper Citation Record · LEDGER

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

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

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

pith.paper-citation-record.v1
2608.07681 v1

Coverage vector

measured 100 of 125 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:31:24.700145Z

measured 100 of 100 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 125 outbound references displayed

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External citation measurements

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Outbound references

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

This paper cites , title =.

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

Reference 1

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

This paper cites an unresolved cited work.

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

Reference 2

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This paper cites and Reinhardt, T.

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

Reference 3

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This paper cites and Albert, R.

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

Reference 4

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This paper cites 2011 , pages =.

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

Reference 5

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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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This paper cites and Wang, X.

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

Reference 13

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

Reference 14

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

Reference 15

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

Reference 16

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

Reference 17

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

Reference 18

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

Reference 19

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

Reference 20

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

Reference 21

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

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

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

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

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

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

Reference 27

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

Reference 28

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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

Reference 31

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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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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=sha256:71e1f56364186950044ef2ab9e10fe1ea58330583517d308d86c69125845e945

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=sha256:63274efce22c7717b117f37894ce6c6540d972b523afce02f3b8a6cfbc2d1cf5

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=sha256:5be56dddeb3f4036e9cfb634a65ba9e3b528b756751d1d61ae72c616d182c606

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=sha256:2bdfdcc7e4eedce3b3daf062b25f0e59fe77e3123fb70841c748c3e5c1a8084e

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=sha256:12bea64c70ffadc1c2be262605c38caf701a50882ac05cb55abaf336324487e4

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:d27aa0b01b78fed38f30ce9d14b104b0ebedc66c2af29c447d84b0e836ef6b2b

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=sha256:80a14f3baaed042311187356c5276d181ed1e97d9e1e4b2052a0223cacaedb58

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

This paper cites Structural Health Monitoring , volume=.

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

Reference 47

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.502883Z digest=sha256:53de5f1ba959e5c48b82a4afb03c82e236aec3dbe1397fcd177deab8dce0ce47

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

This paper cites Journal of Intelligent Manufacturing , volume=.

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

Reference 48

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.506572Z digest=sha256:bd27895fc53bfef313d038220c7023ed882da4f1f7b2d192cc9bfcf32bacc647

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

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

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

Reference 49

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.510787Z digest=sha256:3a495b125b988559fa6a1d5a8009d102469553a262ce7279d96823242f08b5a3

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

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

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

Reference 50

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.513918Z digest=sha256:84e08be4a127e2523612ca796e7354d0bdc95fb82008738ae23f9b889d23eae2

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

This paper cites IEEE access , volume=.

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

Reference 51

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.517236Z digest=sha256:d8d6209317d54e9b483c772e377a1c976b1c54c162e75320ead6c9a4f7d1baa5

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

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

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

Reference 52

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.520816Z digest=sha256:b7eec342eb77be51bb9cf84c4c46b10a498f5586f6725b1097b1039aae8e88c7

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=sha256:76f61670a5f5b9b936825dc91028712d8702eadaa4124075ad70f69d8978fe4d

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

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

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

Reference 54

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.528692Z digest=sha256:bf9b184b3e4499335877ed76273d9f9801787b3a371ebdcf2b8202bc28947af4

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=sha256:754f3834eff6730e604ca9f01f013e566669c46ad155dea11011c0bb512dfd78

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

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

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

Reference 56

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.537508Z digest=sha256:b192db072604b1d8b7065b20fd8e900d0a3c249511bf5c84e8f0b47eeaa70fbe

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=sha256:3590f2c716c4e5c8f84e80eee4a8ae3bf9569d74da6c6394e7946369e70a776c

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

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

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

Reference 58

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.546158Z digest=sha256:575b662c86fe6e2b77aa983c99527a3e977f903c84561651572f44d78846ddd9

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

This paper cites , author=.

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

Reference 59

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.549823Z digest=sha256:2f49bbbc0dcc70e5e711269ff94342a1fe0877cb872f3c3dcc4b78914bd92d24

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

This paper cites Neural Computing and Applications , volume=.

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

Reference 60

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.553491Z digest=sha256:3fd0fd59e036e7d2de6bc006549a5af6a67ebcc547bb3fea1bbdcd85da146dec

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

This paper cites Machine Learning , volume=.

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

Reference 61

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.557177Z digest=sha256:4574c6353bd2bfc1608a7aaf3884c2f7656ef0ebfc2c296d72fd30ac2be6e7f0

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

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

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

Reference 62

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.560803Z digest=sha256:7aff16622ef9ca25d6bf5b8994b6b523a5d72f5e7a3df16de780fbf56c264057

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

This paper cites an unresolved cited work.

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

Reference 63

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.564410Z digest=sha256:157e6ced571280b08ce47cf5a33cfb62f2d4e2753a9320e157c1eff19953598d

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

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

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

Reference 64

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.569231Z digest=sha256:06f5d5bf071c446aa90ede238acd128c5e91adb3784ab269422caf5839003ffa

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

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

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

Reference 65

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.573063Z digest=sha256:4a87d048ed45f0bdb9ebfa8d6e72ed383dd8aeceaca3e39527c4a4416c78f6ed

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=sha256:74829c1de348fa7926ae483c5584d3b8548601a8de33aa8a3eed438874d77616

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=sha256:5e562825213ba57c5672a6cc2f6e24d522d8925e9206061b2242e02662c49080

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

This paper cites , author=.

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

Reference 68

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.584217Z digest=sha256:a0900e15417a9b8d9b5a56a34a5106f787306d45fe0d337c51b53bd61f0baee6

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

This paper cites One Explanation Does Not Fit XIL.

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

Reference 69

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.588155Z digest=sha256:8b358d3e848eccac1384bc6bdfd4bd0a208e8215afd07cd7f0cb44ce2a7ee69c

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

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

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

Reference 70

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.592129Z digest=sha256:f1518085e709bc5516a37ba26e598b7f444dd72ff34ffb1fa4edeeaf9772d7c7

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

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

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

Reference 71

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.595568Z digest=sha256:52b4b3576cfa555650542c65632b6cf924f073d6d3858305c53f5abf00aa58cd

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

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

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

Reference 72

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.599609Z digest=sha256:ea16d8a0a269e042c986ca686cd2f94dce7b820ff17e4abcdd7fd90cb8d4e5ef

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

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

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

Reference 73

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.603272Z digest=sha256:3b917524a2fd35956f7222826679e9570a2a16a401beb7256aadb8df92484109

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

This paper cites Procedia Cirp , volume=.

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

Reference 74

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.607580Z digest=sha256:867888cd08f683e8f96f121eff7bd551673e8825e3fc45f35a72caead65f4846

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

This paper cites Procedia CIRP , volume=.

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

Reference 75

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.612192Z digest=sha256:b3998930645438d6550263d6416d898994a31875ab04d19384ecfcd64af4a083

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

This paper cites Advanced Engineering Informatics , volume=.

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

Reference 76

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.615887Z digest=sha256:41bab039d633d8b19ed5eca425d1d71a65cf8faf388150bf70783ad02bf054da

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

This paper cites The Astrophysical Journal , volume=.

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

Reference 77

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.619840Z digest=sha256:64d4ede088361194f616286a8f336034c06cf354531c4e047718a4367414c2d9

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

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

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

Reference 78

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.623487Z digest=sha256:c0bd508664a81a142599585afe0a95b335ae3eab8a7c3cd6584580b13c0b94a5

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

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

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

Reference 79

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.626982Z digest=sha256:dd38926383c06261594030f59c45fd0a604211c0b19b8e7d8d6971ef7067c77c

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

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

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

Reference 80

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.630458Z digest=sha256:f8914408b94b418a46a7047018d1252befaf4c05af4dd0c1879ddd5578554a8c

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

This paper cites Pattern Recognition , volume=.

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

Reference 81

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.633703Z digest=sha256:473adfe21499385597e0883811978ba1d597fe160cb8f1564063e56af3a357e6

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

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

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

Reference 82

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.636801Z digest=sha256:747fadff9cbeb34645745fa0f464bc76189ddbf53c91f6244e013a22c74dbe32

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

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

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

Reference 83

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.640011Z digest=sha256:4f8b2067e4d387567102628e14a41deef634c8550c2eca9e83cea78e63962223

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

This paper cites Advances in Mechanical Engineering , volume=.

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

Reference 84

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.643218Z digest=sha256:e389be84630c32a9faaa49559727b918c32d4d5e21a141e1d7a4ae4d7c439ee2

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

This paper cites Universe , volume=.

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

Reference 85

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.646298Z digest=sha256:462d035ab6fdfb21470949f95ee5aa0b0d14d433215549be365b6859044aedb5

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=sha256:9ed4bec3ca4fb4fdd4b367b36eabb34ce1d756f4a58a37298ee4bd3995a4ba39

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

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

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

Reference 87

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.652296Z digest=sha256:a629a3a9449a1084780053e6f6b6d0320f0d438328a3d90fdae0a7b833899a84

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

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

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

Reference 88

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.655620Z digest=sha256:e86831dcd0d5ea20a5b32d9263cdeff36b432d12e33140b5a3fae7fc343c9a8f

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=sha256:100ebe35d1371c379f391e3e695be391dc29721dd96d38a695c5f645c4bc2c19

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:a8d4032cbf162c0f267a51f219090df602c9aea999bd0c23a91dce31039563e7

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=sha256:7bc9463dcfd56ddff27423891f43a902cea4dbf64fccca629aedc64bbf3a8565

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

This paper cites Preprints.

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

Reference 92

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.669992Z digest=sha256:27adffc616770edd87ee98ca494c7566527af3c836461f22a86fb1db890f2599

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

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

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

Reference 93

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.673512Z digest=sha256:101ffd428c4d74c81dc94077433645035abd39425df332963c6b73c575b5de59

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

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

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

Reference 94

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.677379Z digest=sha256:71051919355bf413731255202631d4880c18a202effa451394d9eab9ab3cf7fc

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

This paper cites Results in Engineering , volume=.

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

Reference 95

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.681227Z digest=sha256:55c2ca45f98a246c5d8a54f4eec90874c1f51b180721f75e9e6c2221a0ab4388

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

This paper cites Energy , volume=.

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

Reference 96

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.685087Z digest=sha256:c78830eaa5d33d3e7b8b12b5d858fd6c8aaca4fd0f177d22b64cb83e480a61a1

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

This paper cites Energy , pages=.

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

Reference 97

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.688999Z digest=sha256:ba8d18397f98045943f4e6d10d6246b0de76048403b2fa9555b42dba056250e2

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

This paper cites Energy and Buildings , volume=.

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

Reference 98

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.692743Z digest=sha256:d458f3f3f9cc7694dddf82006658fd0c69c5813218c4cb9c83b7f56465a669a9

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

This paper cites IEEE access , volume=.

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

Reference 99

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.696435Z digest=sha256:e5940fc92e1df7d801debf8f759ab71dea24d3ea855252cfc0f6c2d9806189dd

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

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

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

Reference 100

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

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T00:31:24.700145Z digest=sha256:3489bbd4964e3133c57e3b7692d9e4480fdbcd26bc16dfab7f4ba989cc44078d

Pith citing papers

No inbound Pith citation observations are available.