Paper Citation Record · LEDGER

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems

As of 22 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2411.09329.

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

pith.paper-citation-record.v1
2411.09329 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:52:00.796309Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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External citation measurements

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Outbound references

Observation afb7f888-bfb6-45bd-bbfa-64b43aa5b13f · outbound

This paper cites an unresolved cited work.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Unresolved cited work

Reference 1

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This paper cites Abueidda, Qiyue Lu, and Seid Koric.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Abueidda, Qiyue Lu, and Seid Koric

Reference 2

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Observation 0718be3f-5913-4304-82ea-73005476dbb3 · outbound

This paper cites FastVPINNs: An efficient tensor-based Python library for solving partial differential equations using hp-Variational Physics Informed Neural Networks.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems FastVPINNs: An efficient tensor-based Python library for solving partial differential equations using hp-Variational Physics Informed Neural Networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:03.192759Z

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This paper cites FastVPINNs: Tensor-Driven Acceleration of VPINNs for Complex Geometries.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems FastVPINNs: Tensor-Driven Acceleration of VPINNs for Complex Geometries

Reference 4

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Observation e94f6fa4-e91e-48cd-955c-ff736b035fb2 · outbound

This paper cites Workshop report on basic research needs for scientific machine learning: Core technologies for artificial intelligence.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Workshop report on basic research needs for scientific machine learning: Core technologies for artificial intelligence

Reference 5

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Observation 085e9ec0-9b13-4e9c-be83-1cb36799c1b4 · outbound

This paper cites Barrenechea, Volker John, and Petr Knobloch.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Barrenechea, Volker John, and Petr Knobloch

Reference 6

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Observation 886d9a50-c28a-4374-9022-115dd873a9ca · outbound

This paper cites Brooks and Thomas J.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Brooks and Thomas J

Reference 7

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Observation 4b8eca2b-e233-45dc-882a-f54dd1336446 · outbound

This paper cites Scientific machine learning through physics-informed neural networks: where we are and what's next.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Scientific machine learning through physics-informed neural networks: where we are and what's next

Reference 8

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Observation 55828b2c-1a9c-4804-b186-beb75fdac77f · outbound

This paper cites Adaptive finite element methods for parabolic problems.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Adaptive finite element methods for parabolic problems

Reference 9

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Observation aa38062d-cf01-4ec1-be56-a554f9a4d957 · outbound

This paper cites On loss functionals for physics-informed neural networks for steady-state convection-dominated convection-diffusion problems.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems On loss functionals for physics-informed neural networks for steady-state convection-dominated convection-diffusion problems

Reference 10

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Observation c58af2f3-c956-4559-a27f-8b355ebe4694 · outbound

This paper cites On collocation points for physics-informed neural networks applied to convection-dominated convection-diffusion problems.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems On collocation points for physics-informed neural networks applied to convection-dominated convection-diffusion problems

Reference 11

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Observation 971878cb-75af-4755-ac91-610084d13903 · outbound

This paper cites Finite elements.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Finite elements

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:03.084577Z

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Observation 5b0a4e09-1de7-499d-b483-82f89bfac24a · outbound

This paper cites FastVPINNs: A fast, versatile and robust Variational PINNs framework for forward and inverse problems in science.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems FastVPINNs: A fast, versatile and robust Variational PINNs framework for forward and inverse problems in science

Reference 13

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Observation bdc6ccd2-56d8-41b0-a99c-7cead18254be · outbound

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Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Unresolved cited work

Reference 14

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Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Unresolved cited work

Reference 15

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Observation 0079ba1a-1f02-4fac-bf66-18384e8f1036 · outbound

This paper cites On spurious oscillations at layers diminishing ( SOLD ) methods for convection-diffusion equations.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems On spurious oscillations at layers diminishing ( SOLD ) methods for convection-diffusion equations

Reference 16

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Observation 08c7284d-5d26-414b-99b0-0c631b348e3c · outbound

This paper cites On algebraically stabilized schemes for convection-diffusion-reaction problems.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems On algebraically stabilized schemes for convection-diffusion-reaction problems

Reference 17

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Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Unresolved cited work

Reference 18

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Observation 20413c4b-8c8e-4e22-bc0f-c71318a46470 · outbound

This paper cites A posteriori optimization of parameters in stabilized methods for convection-diffusion problems--- P art II.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems A posteriori optimization of parameters in stabilized methods for convection-diffusion problems--- P art II

Reference 19

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Observation 333779f1-5369-4206-9f49-bcd9d25ecb86 · outbound

This paper cites Variational Physics-Informed Neural Networks For Solving Partial Differential Equations.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Variational Physics-Informed Neural Networks For Solving Partial Differential Equations

Reference 20

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Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Unresolved cited work

Reference 21

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Observation b0d614a1-c84c-4c88-bbd6-4ece8f70acaa · outbound

This paper cites Varnet: Variational neural networks for the solution of partial differential equations.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Varnet: Variational neural networks for the solution of partial differential equations

Reference 22

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Observation d927396f-4fde-419b-8b61-468a590dc7d3 · outbound

This paper cites Characterizing possible failure modes in physics-informed neural networks.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Characterizing possible failure modes in physics-informed neural networks

Reference 23

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Observation 8be594b3-ef09-4ce6-8844-3b56712ba62e · outbound

This paper cites Lagaris, A.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Lagaris, A

Reference 24

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Observation 5c548b9b-887f-4643-92a2-bb391d08b657 · outbound

This paper cites Deep XDE : a deep learning library for solving differential equations.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Deep XDE : a deep learning library for solving differential equations

Reference 25

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Observation da349517-0a16-4338-a498-b68f7ddfcaef · outbound

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Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Unresolved cited work

Reference 26

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Observation 0579bd5f-0c2c-4354-a90b-dc2615783a81 · outbound

This paper cites Bound-preserving PINN s for steady-state convection-diffusion-reaction problems.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Bound-preserving PINN s for steady-state convection-diffusion-reaction problems

Reference 27

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Observation 9906e93a-d59c-4062-834a-366356fea9ce · outbound

This paper cites https://developer.nvidia.com/modulus.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems https://developer.nvidia.com/modulus

Reference 28

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Observation b0a26719-7ac6-4f1c-a952-35020120e8ab · outbound

This paper cites Psaros, Xuhui Meng, Zongren Zou, Ling Guo, and George Em Karniadakis.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Psaros, Xuhui Meng, Zongren Zou, Ling Guo, and George Em Karniadakis

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:02.844376Z

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Observation 06084df5-b491-47c1-a7a2-4e63d48e269f · outbound

This paper cites Raissi, P.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Raissi, P

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:02.829543Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5fe0e3d3-6373-4a66-bee4-ec6b117b09e4 · outbound

This paper cites Robust numerical methods for singularly perturbed differential equations, volume 24 of Springer Series in Computational Mathematics.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Robust numerical methods for singularly perturbed differential equations, volume 24 of Springer Series in Computational Mathematics

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:02.814796Z

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Observation 16c56e22-76c2-4a9e-90b1-3ea3089c1804 · outbound

This paper cites Physics informed neural networks with strong and weak residuals for advection-dominated diffusion problems, 2023.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Physics informed neural networks with strong and weak residuals for advection-dominated diffusion problems, 2023

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:02.799002Z

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Observation 53fb20d7-dbf7-48a5-a05b-569872ce643d · outbound

This paper cites Artificial neural network-augmented stabilized finite element method.

Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems Artificial neural network-augmented stabilized finite element method

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:52:02.782501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.