Paper Citation Record · LEDGER

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles

As of 14 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2608.08322.

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

pith.paper-citation-record.v1
2608.08322 v1

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measured 26 of 26 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

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External citation measurements

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Outbound references

Observation 13b0aa15-afdf-4384-b156-5b44f9423c71 · outbound

This paper cites Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations.Journal of Computational Physics, 79(1):12–49, 1988.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations.Journal of Computational Physics, 79(1):12–49, 1988

Reference 1

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Observation 172b0b0d-5925-4d1d-90de-35dc0b36ad4c · outbound

This paper cites A Level Set Approach for Com- puting Solutions to Incompressible Two-Phase Flow.Journal of Computational Physics, 114(1):146–159, 1994.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles A Level Set Approach for Com- puting Solutions to Incompressible Two-Phase Flow.Journal of Computational Physics, 114(1):146–159, 1994

Reference 2

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Observation 31666ef3-036c-46fc-9702-b6fccf81c16e · outbound

This paper cites An Efficient, Interface-Preserving Level Set Re- distancing Algorithm and Its Application to Interfacial Incompressible Fluid Flow.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles An Efficient, Interface-Preserving Level Set Re- distancing Algorithm and Its Application to Interfacial Incompressible Fluid Flow

Reference 3

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Observation d0dfb301-f372-4d6c-b23e-d74c65439709 · outbound

This paper cites Raissi, P.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Raissi, P

Reference 4

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Observation 545df80b-71a2-4e9a-aa5f-ba2e4ac43280 · outbound

This paper cites Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M

Reference 5

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Observation 89f5e251-3f5f-454d-bcec-38c109a4479c · outbound

This paper cites Physics- informed neural networks for solving moving interface flow problems using the level set approach.Physics of Fluids, 37(10):107124, 2025.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Physics- informed neural networks for solving moving interface flow problems using the level set approach.Physics of Fluids, 37(10):107124, 2025

Reference 6

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Observation 52e86073-64f2-49a2-bdf3-42b78def65ac · outbound

This paper cites Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems, 2026.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems, 2026

Reference 7

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Observation 27944279-d60a-4a6f-a681-f452b50557ad · outbound

This paper cites Physics-informed neural networks for solving two-phase flow problems with moving interfaces, 2026.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Physics-informed neural networks for solving two-phase flow problems with moving interfaces, 2026

Reference 8

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Observation b0da4afd-c310-4d5c-b88e-b7d2b244eb89 · outbound

This paper cites Physics-Informed Machine Learning for Two-Phase Moving-Interface and Stefan Problems, 2025.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Physics-Informed Machine Learning for Two-Phase Moving-Interface and Stefan Problems, 2025

Reference 9

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Observation 315f2f93-ec56-4f80-a23d-4048eb9f072f · outbound

This paper cites A systematic study of physics-informed neural networks for the level-set interface advection.Machine Learning: Science and Technology, 7(4):045032, 2026.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles A systematic study of physics-informed neural networks for the level-set interface advection.Machine Learning: Science and Technology, 7(4):045032, 2026

Reference 10

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Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Unresolved cited work

Reference 11

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This paper cites DeepXDE: A Deep Learning Library for Solving Differential Equations.SIAM Review, 63(1):208–228,.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles DeepXDE: A Deep Learning Library for Solving Differential Equations.SIAM Review, 63(1):208–228,

Reference 12

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Observation d6adc7ef-bc6c-48ac-8230-f2a38637c501 · outbound

This paper cites Understanding and Mitigating Gra- dient Flow Pathologies in Physics-Informed Neural Networks.SIAM Journal on Scientific Computing, 43(5):A3055–A3081, 2021.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Understanding and Mitigating Gra- dient Flow Pathologies in Physics-Informed Neural Networks.SIAM Journal on Scientific Computing, 43(5):A3055–A3081, 2021

Reference 13

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Observation 1fe8694e-7850-4a05-a3d4-bd58d00f80ae · outbound

This paper cites Inverse Dirichlet weighting enables reliable training of physics informed neural networks.Machine Learning: Science and Technology, 3(1):015026, 2022.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Inverse Dirichlet weighting enables reliable training of physics informed neural networks.Machine Learning: Science and Technology, 3(1):015026, 2022

Reference 14

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Observation b285613f-13ac-43c8-8527-876ffd369ebf · outbound

This paper cites McClenny and Ulisses M.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles McClenny and Ulisses M

Reference 15

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Observation 7625d21a-0be9-422d-b442-ce1743e07536 · outbound

This paper cites Self-adaptive loss balanced Physics- informed neural networks.Neurocomputing, 496:11–34, 2022.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Self-adaptive loss balanced Physics- informed neural networks.Neurocomputing, 496:11–34, 2022

Reference 16

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Observation d727b49b-22f8-4c39-abfe-5090ebf8bc2c · outbound

This paper cites Efficient Implementation of Weighted ENO Schemes.Journal of Computational Physics, 126(1):202–228, 1996.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Efficient Implementation of Weighted ENO Schemes.Journal of Computational Physics, 126(1):202–228, 1996

Reference 17

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Observation fa932c0d-902f-4ae5-913c-0bf760d551ad · outbound

This paper cites Efficient implementation of essentially non- oscillatory shock-capturing schemes.Journal of Computational Physics, 77(2):439– 471, 1988.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Efficient implementation of essentially non- oscillatory shock-capturing schemes.Journal of Computational Physics, 77(2):439– 471, 1988

Reference 18

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Observation c476eaac-63cf-4565-b67d-8fd5d45d217e · outbound

This paper cites Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T

Reference 19

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Observation f00e3ab7-6717-41da-bbe1-5e48a6b1a591 · outbound

This paper cites Respecting causality for training physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 421:116813, 2024.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Respecting causality for training physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 421:116813, 2024

Reference 20

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Observation 2e727807-fc48-4189-8f93-c1953c100491 · outbound

This paper cites A Hybrid Parti- cle Level Set Method for Improved Interface Capturing.Journal of Computational Physics, 183(1):83–116, 2002.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles A Hybrid Parti- cle Level Set Method for Improved Interface Capturing.Journal of Computational Physics, 183(1):83–116, 2002

Reference 21

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Observation 1c7bc33c-d380-4edb-83de-1982375217e4 · outbound

This paper cites Springer New York, 2003.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Springer New York, 2003

Reference 22

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Observation a02ead75-3762-4c5b-8fc5-5831bdf04926 · outbound

This paper cites When and why PINNs fail to train: A neural tangent kernel perspective.Journal of Computational Physics, 449:110768,.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles When and why PINNs fail to train: A neural tangent kernel perspective.Journal of Computational Physics, 449:110768,

Reference 23

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Observation 60535a67-0f94-46fd-a042-5ee94aed401e · outbound

This paper cites Eikonal regularization in physics-informed neural networks for three-dimensional level-set advection: Transferability of two-dimensional design principles — Source Code, 2026.

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Eikonal regularization in physics-informed neural networks for three-dimensional level-set advection: Transferability of two-dimensional design principles — Source Code, 2026

Reference 24

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Observation 4112c9f1-cdfc-4fc8-a291-30d45de0a733 · outbound

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Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Unresolved cited work

Reference 2021

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Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles Unresolved cited work

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Pith citing papers

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