Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T15:13:11.772226Z
Paper Citation Record · LEDGER
Deep operator network models for predicting post-burn contraction
As of 14 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2411.14555.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
47 of 47 outbound references displayed
- verified exact4
- verified fuzzy36
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 5c0f9aab-cd3a-4754-a731-c299b56a61c6 · outbound
This paper cites Alberts, D.
Deep operator network models for predicting post-burn contraction Alberts, D
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.577703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 0b91d38e-7d97-4aa7-b783-535184af8fee · outbound
This paper cites Chen and H.
Deep operator network models for predicting post-burn contraction Chen and H
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.561131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 87f8586c-4f04-4397-9a3b-f64404ee2181 · outbound
This paper cites DelftBlue Supercomputer (Phase 1).
Deep operator network models for predicting post-burn contraction DelftBlue Supercomputer (Phase 1)
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.544572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 49fdf14b-4ba7-488c-b3ab-e4e964eba5d8 · outbound
This paper cites Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation.
Deep operator network models for predicting post-burn contraction Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.528177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 04a87b35-ac66-4201-b5ea-22c793a85240 · outbound
This paper cites U-DeepONet: U-Net Enhanced Deep Operator Network for Geologic Carbon Sequestration.
Deep operator network models for predicting post-burn contraction U-DeepONet: U-Net Enhanced Deep Operator Network for Geologic Carbon Sequestration
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T15:13:11.940300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b5c1fc7a-bd61-473f-bf9d-fcf347518ce0 · outbound
This paper cites A Bayesian finite- element trained machine learning approach for predicting post-burn contraction.
Deep operator network models for predicting post-burn contraction A Bayesian finite- element trained machine learning approach for predicting post-burn contraction
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.510821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f9600f2d-7716-4929-a9d5-f5e57a4367c7 · outbound
This paper cites Some mathematical properties of morphoelasticity.
Deep operator network models for predicting post-burn contraction Some mathematical properties of morphoelasticity
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.494642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 7eb21398-e88a-4b68-82f4-ae30af2709da · outbound
This paper cites Sensitivity and feasibility of a one-dimen- sional morphoelastic model for post-burn contraction.
Deep operator network models for predicting post-burn contraction Sensitivity and feasibility of a one-dimen- sional morphoelastic model for post-burn contraction
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.479092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 7d4132c3-4dfa-4892-9259-f8412d75a238 · outbound
This paper cites High-speed predictions of post-burn con- traction using a neural network trained on 2d-finite element simulations.
Deep operator network models for predicting post-burn contraction High-speed predictions of post-burn con- traction using a neural network trained on 2d-finite element simulations
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.463386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 846efe1d-197d-420b-950f-f95844a6ae46 · outbound
This paper cites Deep learning.
Deep operator network models for predicting post-burn contraction Deep learning
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.446727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c47d3e1f-5612-4ade-b4e0-a4620b91a284 · outbound
This paper cites an unresolved cited work.
Deep operator network models for predicting post-burn contraction Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T15:13:12.430629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation af134c88-8a24-429f-88e8-a986192600e0 · outbound
This paper cites Preconditioned FEM-based Neural Networks for Solving Incompressible Fluid Flows and Related Inverse Problems.
Deep operator network models for predicting post-burn contraction Preconditioned FEM-based Neural Networks for Solving Incompressible Fluid Flows and Related Inverse Problems
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T15:13:11.916263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 46f40a8c-e64e-4f75-af5c-7d26278e48cb · outbound
This paper cites Modelling of some biological materials using continuum mechanics.
Deep operator network models for predicting post-burn contraction Modelling of some biological materials using continuum mechanics
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.414663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6fa088ba-02b1-4818-a7ee-ef959d604340 · outbound
This paper cites Multifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems.
Deep operator network models for predicting post-burn contraction Multifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:13:11.599663Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e4e9cb8-5d22-48e0-b314-7d005fa9f76d · outbound
This paper cites A user’s guide to pde models for chemotaxis.
Deep operator network models for predicting post-burn contraction A user’s guide to pde models for chemotaxis
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.398968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8f6e17a0-a81a-4139-9fbe-5aa456854a3c · outbound
This paper cites Stacked networks improve physics-informed training: applications to neural networks and deep operator networks.
Deep operator network models for predicting post-burn contraction Stacked networks improve physics-informed training: applications to neural networks and deep operator networks
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:13:11.609522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f57242cd-95a0-4234-9a44-865a8308ca3a · outbound
This paper cites The application of neural operators to predict skin evolution after burn trauma.
Deep operator network models for predicting post-burn contraction The application of neural operators to predict skin evolution after burn trauma
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.382398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 58b499cd-22a0-43b0-8c97-703a6f44d484 · outbound
This paper cites ICRP Publication 110.
Deep operator network models for predicting post-burn contraction ICRP Publication 110
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.366456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1a1ac42b-d222-47bb-8e08-6bfdcd3b46d4 · outbound
This paper cites an unresolved cited work.
Deep operator network models for predicting post-burn contraction Unresolved cited work
Reference 19
- Resolution
- verified exact
- doi, observed 2026-08-12T15:13:11.811510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8fd6f15d-b14c-4d43-b1f7-bc44a9ecf452 · outbound
This paper cites Kingma and Jimmy Ba.
Deep operator network models for predicting post-burn contraction Kingma and Jimmy Ba
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.350513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2c61e71f-b49d-415a-9940-da33243c370f · outbound
This paper cites DeepOnet Based Preconditioning Strategies For Solving Parametric Linear Systems of Equations.
Deep operator network models for predicting post-burn contraction DeepOnet Based Preconditioning Strategies For Solving Parametric Linear Systems of Equations
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:13:11.636319Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf8fd18c-e48e-4e3d-8ebf-ff566341791e · outbound
This paper cites Koppenol.
Deep operator network models for predicting post-burn contraction Koppenol
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.335371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f25343f2-6e20-4790-bcce-3deed6281871 · outbound
This paper cites Koppenol and F.
Deep operator network models for predicting post-burn contraction Koppenol and F
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.319718Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5ef68bea-d02c-4256-b3bd-2ff7b34f4fe8 · outbound
This paper cites A mathematical model for the simulation of the formation and the subsequent regression of hyper- trophic scar tissue after dermal wounding.
Deep operator network models for predicting post-burn contraction A mathematical model for the simulation of the formation and the subsequent regression of hyper- trophic scar tissue after dermal wounding
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.302835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 42b3d355-5edc-48b9-8a5e-65c21ffa9753 · outbound
This paper cites Neural operator: Learning maps between function spaces.
Deep operator network models for predicting post-burn contraction Neural operator: Learning maps between function spaces
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.287059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6a4fbda4-3e72-4211-8d1a-d35a50739c8d · outbound
This paper cites Lagaris, A.
Deep operator network models for predicting post-burn contraction Lagaris, A
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.270428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation dc37d2b6-d189-4552-830d-bf564c3455df · outbound
This paper cites Fourier neural operator for parametric partial differential equations.
Deep operator network models for predicting post-burn contraction Fourier neural operator for parametric partial differential equations
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.255071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 18bca267-6db1-4428-9857-28000f51e3e8 · outbound
This paper cites Liu and Jorge Nocedal.
Deep operator network models for predicting post-burn contraction Liu and Jorge Nocedal
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.239504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3f67a363-1594-4679-9eab-50660f5a00c9 · outbound
This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.
Deep operator network models for predicting post-burn contraction DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.224391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f7f4deef-c000-46f0-bd34-a78d2bff6919 · outbound
This paper cites Maskarinec, C.
Deep operator network models for predicting post-burn contraction Maskarinec, C
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.207913Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6732dca7-2150-4fb4-b680-fc0afa798ea1 · outbound
This paper cites Meethal, Anoop Kodakkal, Mohamed Khalil, Aditya Ghantasala, Birgit Obst, Kai-Uwe Bletzinger, and Roland W¨ uchner.
Deep operator network models for predicting post-burn contraction Meethal, Anoop Kodakkal, Mohamed Khalil, Aditya Ghantasala, Birgit Obst, Kai-Uwe Bletzinger, and Roland W¨ uchner
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.188584Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 73f83f9d-d5d1-4f61-bff7-d42e635de531 · outbound
This paper cites Physics-informed machine learning embedded into isogeometric analysis.
Deep operator network models for predicting post-burn contraction Physics-informed machine learning embedded into isogeometric analysis
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.171867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a5e597da-a62c-43c4-8b0e-5900c1795fe1 · outbound
This paper cites M¨ oller, D.
Deep operator network models for predicting post-burn contraction M¨ oller, D
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.155241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 000d1516-b25d-4bb0-b713-eb7dd1462b1d · outbound
This paper cites Olsen, J.
Deep operator network models for predicting post-burn contraction Olsen, J
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.138382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b82646d7-66b6-4549-ab8b-a3620e816e38 · outbound
This paper cites Overall, J.
Deep operator network models for predicting post-burn contraction Overall, J
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.121785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 89589985-7400-4b01-8356-38f09caa31f9 · outbound
This paper cites Raissi, P.
Deep operator network models for predicting post-burn contraction Raissi, P
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:13:11.716204Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d409482-f738-4cf5-b29a-ccb767b5876a · outbound
This paper cites Convolutional neural operators for robust and accurate learning of PDEs.
Deep operator network models for predicting post-burn contraction Convolutional neural operators for robust and accurate learning of PDEs
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.094983Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 949106a1-55cb-4602-8889-a282c72e16e9 · outbound
This paper cites Roberts, M.
Deep operator network models for predicting post-burn contraction Roberts, M
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.078278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5bd5ba3e-760c-4b4e-b8dc-f3546623fd97 · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation.
Deep operator network models for predicting post-burn contraction U-net: Convolutional networks for biomedical image segmentation
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:13:11.731119Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62ca2288-a831-42b6-9333-a67d425c7e4c · outbound
This paper cites Rudolph and J.
Deep operator network models for predicting post-burn contraction Rudolph and J
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.050004Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e374b84d-d141-4f82-a933-7312de6fae2d · outbound
This paper cites Strutz, M.
Deep operator network models for predicting post-burn contraction Strutz, M
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.034316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 45267f8f-8ac7-41bc-8dc2-3e7035477af9 · outbound
This paper cites DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems, September.
Deep operator network models for predicting post-burn contraction DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems, September
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.018172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation bb5883ec-490c-44c4-acd0-737e15ad059f · outbound
This paper cites Vande Berg, R.
Deep operator network models for predicting post-burn contraction Vande Berg, R
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:12.001266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 46f8b172-59d6-46e3-ad2d-5fb3f93d6753 · outbound
This paper cites Learning the solution operator of parametric partial differential equations with physics-informed deeponets.
Deep operator network models for predicting post-burn contraction Learning the solution operator of parametric partial differential equations with physics-informed deeponets
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:13:11.761518Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd6657af-f591-45b8-a917-816f43c8d3a3 · outbound
This paper cites Chung, Yalchin Efendiev, and Min Wang.
Deep operator network models for predicting post-burn contraction Chung, Yalchin Efendiev, and Min Wang
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:11.973694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 34aa5659-9340-41f1-9887-e6a993ad96ae · outbound
This paper cites Wrobel, T.
Deep operator network models for predicting post-burn contraction Wrobel, T
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:13:11.956952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation bdc695b1-00fe-40cc-b6f0-c8bacaa2f4a2 · outbound
This paper cites DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems.
Deep operator network models for predicting post-burn contraction DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems
Reference 2022
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T15:13:11.836190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Pith citing papers
No inbound Pith citation observations are available.