Paper Citation Record · LEDGER

Learning cardiac activation and repolarization times with operator learning

As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.08631.

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

pith.paper-citation-record.v1
2505.08631 v1

Coverage vector

measured 44 of 44 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

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Reference resolution

44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation 4f0d335a-2edd-4ce6-bbb0-5889264076ea · outbound

This paper cites lifex: A flexible, high performance library for the numerical solution of complex finite element problems.SoftwareX20 (2022): 101252.

Learning cardiac activation and repolarization times with operator learning lifex: A flexible, high performance library for the numerical solution of complex finite element problems.SoftwareX20 (2022): 101252

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.448187Z

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Observation 3b177977-98a1-45b3-97ee-851a87563b8e · outbound

This paper cites Al-Khatib, Dan M.

Learning cardiac activation and repolarization times with operator learning Al-Khatib, Dan M

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.436705Z

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Observation ca068823-bc6e-4ee4-9a71-4cc4926f5174 · outbound

This paper cites PETSc users manual.

Learning cardiac activation and repolarization times with operator learning PETSc users manual

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.424923Z

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Observation 9ab10dc3-c75c-402e-a612-0f3ddb227bbc · outbound

This paper cites Kernel methods are com- petitive for operator learning.Journal of Computational Physics496 (2024): 112549.

Learning cardiac activation and repolarization times with operator learning Kernel methods are com- petitive for operator learning.Journal of Computational Physics496 (2024): 112549

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.413191Z

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Observation 2f2e82f6-ca6f-4a0a-a468-b1aff76fbf9d · outbound

This paper cites The lifex library version 2.0.

Learning cardiac activation and repolarization times with operator learning The lifex library version 2.0

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:28.683126Z

Source-reported events for the cited work

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Observation 2bbadfab-f483-4ada-8197-7c589c83c3f8 · outbound

This paper cites A comparison of Algebraic Multigrid Bidomain solvers on hybrid CPU–GPU architectures.Computer Methods in Applied Mechanics and Engineering 423 (2024): 116875.

Learning cardiac activation and repolarization times with operator learning A comparison of Algebraic Multigrid Bidomain solvers on hybrid CPU–GPU architectures.Computer Methods in Applied Mechanics and Engineering 423 (2024): 116875

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.402045Z

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Observation 182c7abe-ac41-4200-ad78-a4874483aa78 · outbound

This paper cites Pavarino.

Learning cardiac activation and repolarization times with operator learning Pavarino

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.391550Z

Source-reported events for the cited work

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Observation a44a4cec-9bdc-4ef2-bc44-41cd241373a5 · outbound

This paper cites H., Olivier Bernus, E.

Learning cardiac activation and repolarization times with operator learning H., Olivier Bernus, E

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.380317Z

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Observation 0cad749c-d4a7-4106-813f-240d7c204a15 · outbound

This paper cites Pavarino, and Simone Scacchi.

Learning cardiac activation and repolarization times with operator learning Pavarino, and Simone Scacchi

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.368469Z

Source-reported events for the cited work

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Observation 7c68e5a9-d263-4527-85d6-ad1daf7ffcd0 · outbound

This paper cites Wavefront propagation in an activation model of the anisotropic cardiac tissue: asymptotic analysis and numerical simulations.Journal of mathematical biology28 (1990): 121-176.

Learning cardiac activation and repolarization times with operator learning Wavefront propagation in an activation model of the anisotropic cardiac tissue: asymptotic analysis and numerical simulations.Journal of mathematical biology28 (1990): 121-176

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.354497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d2042342-0fae-4e2d-952e-b2488e61d12e · outbound

This paper cites an unresolved cited work.

Learning cardiac activation and repolarization times with operator learning Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:54:29.341250Z

Source-reported events for the cited work

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Observation 777786e9-3093-4d5c-bca6-8a4b9f6ec407 · outbound

This paper cites Delving deep into rectifiers: Surpass- ing human-level performance on imagenet classification.

Learning cardiac activation and repolarization times with operator learning Delving deep into rectifiers: Surpass- ing human-level performance on imagenet classification

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.328215Z

Source-reported events for the cited work

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Observation 3faaa729-60f4-469c-b921-230fe78fb91a · outbound

This paper cites Impulses and physiological states in theoretical models of nerve membrane.

Learning cardiac activation and repolarization times with operator learning Impulses and physiological states in theoretical models of nerve membrane

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.315809Z

Source-reported events for the cited work

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Observation e0d7dce5-ba6b-40f4-a0c7-4aa3ec64a7ff · outbound

This paper cites Deep learning-based reduced order models in cardiac electrophysiology.PloS one15, no.

Learning cardiac activation and repolarization times with operator learning Deep learning-based reduced order models in cardiac electrophysiology.PloS one15, no

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.303595Z

Source-reported events for the cited work

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Observation cbaeb302-e952-4c21-9e47-ce0a5b47f7d0 · outbound

This paper cites A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials.Computer Methods in Applied Mechanics and Engineering391 (2022): 114587.

Learning cardiac activation and repolarization times with operator learning A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials.Computer Methods in Applied Mechanics and Engineering391 (2022): 114587

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.290937Z

Source-reported events for the cited work

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Observation b4b439d9-1260-4b81-bb20-df17e4aa4f0e · outbound

This paper cites Fitzhugh-nagumo model.Scholarpedia1, no.

Learning cardiac activation and repolarization times with operator learning Fitzhugh-nagumo model.Scholarpedia1, no

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.278106Z

Source-reported events for the cited work

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Observation 416cda72-de6d-457d-b053-521c7905a30c · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.Advances in neural information processing systems31 (2018).

Learning cardiac activation and repolarization times with operator learning Neural tangent kernel: Convergence and generalization in neural networks.Advances in neural information processing systems31 (2018)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.265870Z

Source-reported events for the cited work

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Observation 044d4da9-40f4-4beb-ad75-ba103ee6dd50 · outbound

This paper cites P., and James Sneyd.Mathematical physiology1: Cellular physiology.

Learning cardiac activation and repolarization times with operator learning P., and James Sneyd.Mathematical physiology1: Cellular physiology

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.253343Z

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Observation 245bc4dd-995f-4ff5-a54d-5737d8ac9110 · outbound

This paper cites An eikonal-curvature equation for action potential propagation in myocardium.

Learning cardiac activation and repolarization times with operator learning An eikonal-curvature equation for action potential propagation in myocardium

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.240425Z

Source-reported events for the cited work

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Observation 15296324-4f1c-4a91-a3db-b0b44e286cd3 · outbound

This paper cites Witschey, John A.

Learning cardiac activation and repolarization times with operator learning Witschey, John A

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.227530Z

Source-reported events for the cited work

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Observation b940bcc9-c893-4944-a5ec-f47048bc3334 · outbound

This paper cites On universal approximation and error bounds for Fourier neural operators.The Journal of Machine Learning Research22, no.

Learning cardiac activation and repolarization times with operator learning On universal approximation and error bounds for Fourier neural operators.The Journal of Machine Learning Research22, no

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.215149Z

Source-reported events for the cited work

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Observation 21ed8985-75b8-46aa-a2dc-e6e029458b2c · outbound

This paper cites Neural operator: Learning maps between function spaces with applications to PDEs.Journal of Machine Learning Research24, no.

Learning cardiac activation and repolarization times with operator learning Neural operator: Learning maps between function spaces with applications to PDEs.Journal of Machine Learning Research24, no

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.200621Z

Source-reported events for the cited work

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Observation d7bafa5d-6f8c-448f-a2f0-7cef31f733e8 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Learning cardiac activation and repolarization times with operator learning Fourier Neural Operator for Parametric Partial Differential Equations

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:28.752265Z

Source-reported events for the cited work

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Observation 007977fc-1585-4b37-9bbb-3166d46a3a69 · outbound

This paper cites Michelis, Emmanuel de Bezenac, Sirani M.

Learning cardiac activation and repolarization times with operator learning Michelis, Emmanuel de Bezenac, Sirani M

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:28.756182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff5a7707-f0fc-4428-ad3e-d05e453fc769 · outbound

This paper cites Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators.

Learning cardiac activation and repolarization times with operator learning Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.187560Z

Source-reported events for the cited work

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Observation 9028390e-56ca-4025-8b77-eda3ac0aa5c3 · outbound

This paper cites A comprehensive and fair comparison of two neural operators (with practical extensions) based on fair data.Computer Methods in Applied Mechanics and Engineering 393 (2022): 114778.

Learning cardiac activation and repolarization times with operator learning A comprehensive and fair comparison of two neural operators (with practical extensions) based on fair data.Computer Methods in Applied Mechanics and Engineering 393 (2022): 114778

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.175118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fc1137e4-47d7-4eb8-842f-77ea358df713 · outbound

This paper cites Kernel methods through the roof: handling billions of points efficiently.Advances in Neural Information Pro- cessing Systems33 (2020): 14410-14422.

Learning cardiac activation and repolarization times with operator learning Kernel methods through the roof: handling billions of points efficiently.Advances in Neural Information Pro- cessing Systems33 (2020): 14410-14422

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.162198Z

Source-reported events for the cited work

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Observation 696cc165-908a-4c38-99d8-a9b194a82378 · outbound

This paper cites Kernel flows: From learning kernels from data into the abyss.Journal of Computational Physics389 (2019): 22-47.

Learning cardiac activation and repolarization times with operator learning Kernel flows: From learning kernels from data into the abyss.Journal of Computational Physics389 (2019): 22-47

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.149441Z

Source-reported events for the cited work

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Observation 48623f21-773d-4251-bf62-79d137c5d2e5 · outbound

This paper cites an unresolved cited work.

Learning cardiac activation and repolarization times with operator learning Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:54:29.136819Z

Source-reported events for the cited work

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Observation 6f697ad4-d450-46a1-82c5-cda904104d42 · outbound

This paper cites Learn- ing the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks.Na- ture Communications15, no.

Learning cardiac activation and repolarization times with operator learning Learn- ing the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks.Na- ture Communications15, no

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.124370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9a76c951-8eb8-443b-90b3-52b731fe75d7 · outbound

This paper cites McCulloch.

Learning cardiac activation and repolarization times with operator learning McCulloch

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.111449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 216cb28c-5bc1-45d2-a0be-26139a40e061 · outbound

This paper cites Cajas, Eva Casoni, and Mariano V´ azquez.

Learning cardiac activation and repolarization times with operator learning Cajas, Eva Casoni, and Mariano V´ azquez

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.099129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8550ec09-d929-439c-8e88-fa2992216804 · outbound

This paper cites Iterative kernel regression with preconditioning.Analysis and Appli- cations22, no.

Learning cardiac activation and repolarization times with operator learning Iterative kernel regression with preconditioning.Analysis and Appli- cations22, no

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.086879Z

Source-reported events for the cited work

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Observation b8c4502b-e736-4650-a80c-d9046de9cb90 · outbound

This paper cites The connection between regular- ization operators and support vector kernels.Neural networks11.4 (1998): 637-649.

Learning cardiac activation and repolarization times with operator learning The connection between regular- ization operators and support vector kernels.Neural networks11.4 (1998): 637-649

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.075321Z

Source-reported events for the cited work

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Observation 6fb1eaff-b4d6-413c-8291-4e890647fe51 · outbound

This paper cites Computing the electrical activity in the heart.Springer Science & Business Media.

Learning cardiac activation and repolarization times with operator learning Computing the electrical activity in the heart.Springer Science & Business Media

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.063201Z

Source-reported events for the cited work

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Observation bc710fa3-45c2-45d1-9c67-07a1f45a115b · outbound

This paper cites Panfilov.

Learning cardiac activation and repolarization times with operator learning Panfilov

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.051045Z

Source-reported events for the cited work

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Observation caaf25aa-463e-4929-b3e2-35aa205f8d1d · outbound

This paper cites PDE-aware deep learning for inverse problems in cardiac electrophysiology.SIAM Journal on Scientific Computing 44, no.

Learning cardiac activation and repolarization times with operator learning PDE-aware deep learning for inverse problems in cardiac electrophysiology.SIAM Journal on Scientific Computing 44, no

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.038676Z

Source-reported events for the cited work

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Observation 5e2d45b5-d5a7-4d28-a8e9-7c97f95ddb31 · outbound

This paper cites Popescu, and Julie K.

Learning cardiac activation and repolarization times with operator learning Popescu, and Julie K

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.026318Z

Source-reported events for the cited work

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Observation 4c64f546-9666-406e-b725-bd2d9aef2dcb · outbound

This paper cites A., Lyon, A., Shade, J., and Heijman, J.

Learning cardiac activation and repolarization times with operator learning A., Lyon, A., Shade, J., and Heijman, J

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:29.014407Z

Source-reported events for the cited work

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Observation 1290561c-e203-47a5-9a92-0cd8fc2c4d3d · outbound

This paper cites an unresolved cited work.

Learning cardiac activation and repolarization times with operator learning Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:54:29.002034Z

Source-reported events for the cited work

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Observation b43fa1d2-03e4-4fd5-9e62-e1e97809bafd · outbound

This paper cites Cardiac ventricular repolarization reserve: a principle for understanding drug-related proarrhythmic risk.British journal of pharmacology164, no.

Learning cardiac activation and repolarization times with operator learning Cardiac ventricular repolarization reserve: a principle for understanding drug-related proarrhythmic risk.British journal of pharmacology164, no

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:28.990110Z

Source-reported events for the cited work

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Observation 5c04cff7-5bad-4b33-ba16-74d5a5b00aa1 · outbound

This paper cites Frangi, and Alfio Quarteroni.

Learning cardiac activation and repolarization times with operator learning Frangi, and Alfio Quarteroni

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:28.977760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f5b8aea3-78f1-4f97-9453-c13f377181cc · outbound

This paper cites an unresolved cited work.

Learning cardiac activation and repolarization times with operator learning Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:54:28.964861Z

Source-reported events for the cited work

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Observation 9fa16acf-567a-4892-bcb9-911b04bacfce · outbound

This paper cites Learning epidemic trajectories through Kernel Operator Learning: from modelling to optimal control.Numerical Mathematics: Theory, Methods and Applications(2025): 104208.

Learning cardiac activation and repolarization times with operator learning Learning epidemic trajectories through Kernel Operator Learning: from modelling to optimal control.Numerical Mathematics: Theory, Methods and Applications(2025): 104208

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:28.951922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.