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Paper Citation Record · LEDGER

Complex Physics-Informed Neural Network

As of 10 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 2 inbound Pith citation observations for arXiv:2502.04917.

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

pith.paper-citation-record.v1
2502.04917 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:06:33.543190Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:41:24.537783Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:51:30.184815Z

Reference resolution

52 of 52 outbound references displayed

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External citation measurements

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Outbound references

Observation b7b9e903-08e9-4bea-878a-943fdbb7402b · outbound

This paper cites Raissi, P.

Complex Physics-Informed Neural Network Raissi, P

Reference 1

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Observation 9609ea41-70a9-4300-83b6-14b626372923 · outbound

This paper cites Physics- informed machine learning.

Complex Physics-Informed Neural Network Physics- informed machine learning

Reference 2

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Observation eae0cbe2-d94c-4877-965a-9057cb616cb5 · outbound

This paper cites Physics-informed neural networks for inverse problems in nano-optics and metamaterials.

Complex Physics-Informed Neural Network Physics-informed neural networks for inverse problems in nano-optics and metamaterials

Reference 3

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Observation 2d450457-9b2f-408c-8b58-7d2a2fa0cff4 · outbound

This paper cites Non-invasive inference of thrombus material properties with physics-informed neural networks.

Complex Physics-Informed Neural Network Non-invasive inference of thrombus material properties with physics-informed neural networks

Reference 4

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Observation 45d62a6f-bd0a-4fb9-8f4c-f630e9e19661 · outbound

This paper cites Physics-informed neural networks for heat transfer problems.

Complex Physics-Informed Neural Network Physics-informed neural networks for heat transfer problems

Reference 5

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Observation d0a203d3-9516-4a38-87ad-fcfd2784a024 · outbound

This paper cites Heat transfer prediction with unknown thermal boundary conditions using physics-informed neural networks.

Complex Physics-Informed Neural Network Heat transfer prediction with unknown thermal boundary conditions using physics-informed neural networks

Reference 6

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 994ac7dd-bb91-46e2-a05f-d664a58c5be4 · outbound

This paper cites Physics-informed graph convolutional neural network for modeling fluid flow and heat convection.

Complex Physics-Informed Neural Network Physics-informed graph convolutional neural network for modeling fluid flow and heat convection

Reference 7

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 43ec0420-080a-4d4d-899c-7047ec41a3fc · outbound

This paper cites A physics-informed neural network technique based on a modified loss function for computational 2D and 3D solid mechanics.Computational Mechanics, 71(3):543–562, 2023.

Complex Physics-Informed Neural Network A physics-informed neural network technique based on a modified loss function for computational 2D and 3D solid mechanics.Computational Mechanics, 71(3):543–562, 2023

Reference 8

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Observation 329e2b03-645e-4f7e-b1af-b6f00963ce73 · outbound

This paper cites A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics.

Complex Physics-Informed Neural Network A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics

Reference 9

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Observation 6a3e7692-0efa-4390-82d9-0a3b6288e984 · outbound

This paper cites Analyses of internal structures and defects in materials using physics-informed neural networks.

Complex Physics-Informed Neural Network Analyses of internal structures and defects in materials using physics-informed neural networks

Reference 10

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Observation 27dc0c11-8e5e-4b20-be68-4c3d2c7c051b · outbound

This paper cites Physics-informed neural networks (PINNs) for fluid mechanics: A review.

Complex Physics-Informed Neural Network Physics-informed neural networks (PINNs) for fluid mechanics: A review

Reference 11

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Observation 9f67226b-aa61-4d1a-ab6f-b1357b75548b · outbound

This paper cites NSFnets (Navier-Stokes flow nets): Physics- informed neural networks for the incompressible Navier-Stokes equations.

Complex Physics-Informed Neural Network NSFnets (Navier-Stokes flow nets): Physics- informed neural networks for the incompressible Navier-Stokes equations

Reference 12

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c909a982-3823-4122-9d83-bbde35fb2f64 · outbound

This paper cites Physics-informed neural networks for inverse problems in supersonic flows.

Complex Physics-Informed Neural Network Physics-informed neural networks for inverse problems in supersonic flows

Reference 13

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 85707a9b-c995-4230-b39c-5c68a43eebfa · outbound

This paper cites Stochastic physics-informed neural ordinary differential equations.

Complex Physics-Informed Neural Network Stochastic physics-informed neural ordinary differential equations

Reference 14

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Observation 460a8288-451c-4225-916c-67e55b99a758 · outbound

This paper cites Physics-informed generative adversarial networks for stochastic differential equations.

Complex Physics-Informed Neural Network Physics-informed generative adversarial networks for stochastic differential equations

Reference 15

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raw_fallback, observed 2026-08-08T21:06:34.175223Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c619a0b1-ddd7-452e-bdb9-4548794fd392 · outbound

This paper cites Adversarial uncertainty quantification in physics-informed neural networks.

Complex Physics-Informed Neural Network Adversarial uncertainty quantification in physics-informed neural networks

Reference 16

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation cfc86bfe-da1e-47cb-ba9a-bb21573fead2 · outbound

This paper cites B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data.

Complex Physics-Informed Neural Network B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data

Reference 17

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2369a216-012a-48ed-a577-e7f4d689df89 · outbound

This paper cites Understanding and mitigating gradient flow pathologies in physics-informed neural networks.

Complex Physics-Informed Neural Network Understanding and mitigating gradient flow pathologies in physics-informed neural networks

Reference 18

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Observation b9539239-0e00-4841-b038-6de16dc1a7fe · outbound

This paper cites When and why PINNs fail to train: A neural tangent kernel perspective.

Complex Physics-Informed Neural Network When and why PINNs fail to train: A neural tangent kernel perspective

Reference 19

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Observation 3c6f273a-588b-460f-9bbb-dcfb426ff4f0 · outbound

This paper cites Numerical Analysis (10th).

Complex Physics-Informed Neural Network Numerical Analysis (10th)

Reference 20

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4344c029-82d9-47ae-9748-ac7e9b900c88 · outbound

This paper cites Self-adaptive physics-informed neural networks.

Complex Physics-Informed Neural Network Self-adaptive physics-informed neural networks

Reference 21

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Observation fea89d80-37b4-4d5d-8f13-7feb75ef9499 · outbound

This paper cites Loss-attentional physics-informed neural networks.

Complex Physics-Informed Neural Network Loss-attentional physics-informed neural networks

Reference 22

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ea9d2cc2-c293-4e3c-a7bf-fb658835ce72 · outbound

This paper cites DeepXDE: A deep learning library for solving differential equations.

Complex Physics-Informed Neural Network DeepXDE: A deep learning library for solving differential equations

Reference 23

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raw_fallback, observed 2026-08-08T21:06:34.062543Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fc697e1a-3208-4e11-9f42-09b4c4164575 · outbound

This paper cites A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks.

Complex Physics-Informed Neural Network A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Reference 24

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Observation f173f87f-96f7-43a4-ac15-21668d24d7b3 · outbound

This paper cites Active learning based sampling for high-dimensional nonlinear partial differential equations.

Complex Physics-Informed Neural Network Active learning based sampling for high-dimensional nonlinear partial differential equations

Reference 25

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6ff6ee51-d7a2-4505-a932-c258ff8f75a3 · outbound

This paper cites Failure-informed adaptive sampling for PINNs.SIAM Journal on Scientific Computing, 45(4):A1971–A1994, 2023.

Complex Physics-Informed Neural Network Failure-informed adaptive sampling for PINNs.SIAM Journal on Scientific Computing, 45(4):A1971–A1994, 2023

Reference 26

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raw_fallback, observed 2026-08-08T21:06:34.018664Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6c574fc8-c78d-4514-9337-283426f003af · outbound

This paper cites Respecting causality for training physics-informed neural networks.

Complex Physics-Informed Neural Network Respecting causality for training physics-informed neural networks

Reference 27

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raw_fallback, observed 2026-08-08T21:06:34.002691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.415469Z digest=sha256:cfa4060f965fb3729d2c8ff2f903e6e049cc2fba4751be40c326ab00718f7614

Observation da8cb5d7-98e1-46cd-8e4b-a1e3c4ca84e5 · outbound

This paper cites Mitigating propagation failures in physics- informed neural networks using retain-resample-release (R3) sampling.

Complex Physics-Informed Neural Network Mitigating propagation failures in physics- informed neural networks using retain-resample-release (R3) sampling

Reference 28

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raw_fallback, observed 2026-08-08T21:06:33.986947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3506630a-d438-4109-95b4-51c68619764b · outbound

This paper cites Extended physics-informed neural networks (XPINNs): A generalized space-time domain decomposition based deep learning framework for nonlinear partial differential equations.

Complex Physics-Informed Neural Network Extended physics-informed neural networks (XPINNs): A generalized space-time domain decomposition based deep learning framework for nonlinear partial differential equations

Reference 29

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raw_fallback, observed 2026-08-08T21:06:33.971449Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 355deff8-6331-4be5-875b-60a4b88ce284 · outbound

This paper cites Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems.

Complex Physics-Informed Neural Network Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems

Reference 30

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source=pdf_text observed=2026-08-08T21:06:33.432668Z digest=sha256:5deb8054e4134c2db25a95375313742fdb24bf34c2d0f8f8b3643bf5074aace0

Observation 58e23747-071c-4497-820e-d75e6b7542ca · outbound

This paper cites Parallel physics-informed neural networks via domain decomposition.

Complex Physics-Informed Neural Network Parallel physics-informed neural networks via domain decomposition

Reference 31

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no resolver link, observed 2026-08-08T21:06:33.438369Z

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source=pdf_text observed=2026-08-08T21:06:33.438369Z digest=sha256:650e0692d6810c95a8e822b0c6e697c35ac49f51520072ef95eb20fc1ea306c0

Observation c7a52acb-53a2-4503-bcc0-33c3a39a13c7 · outbound

This paper cites Initialization-enhanced physics-informed neural network with domain decomposition (IDPINN).

Complex Physics-Informed Neural Network Initialization-enhanced physics-informed neural network with domain decomposition (IDPINN)

Reference 32

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raw_fallback, observed 2026-08-08T21:06:33.935821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 01525e0e-14c6-46f9-ae30-78cca8a480d3 · outbound

This paper cites Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers.

Complex Physics-Informed Neural Network Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers

Reference 33

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no resolver link, observed 2026-08-08T21:06:33.447415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:06:33.447415Z digest=sha256:5b749a36f48d65a944646fa1c242f71445a652e8d3bf0ba0b302865310b4ca96

Observation 9769fd57-c623-4f29-81ea-c83540c8eb14 · outbound

This paper cites Two-stage initial-value iterative physics- informed neural networks for simulating solitary waves of nonlinear wave equations.

Complex Physics-Informed Neural Network Two-stage initial-value iterative physics- informed neural networks for simulating solitary waves of nonlinear wave equations

Reference 34

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raw_fallback, observed 2026-08-08T21:06:33.920782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 9895dc76-1398-4f07-a955-4601aa979425 · outbound

This paper cites Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems.

Complex Physics-Informed Neural Network Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

Reference 35

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raw_fallback, observed 2026-08-08T21:06:33.905571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.458190Z digest=sha256:80860e2678a9907b7698bdf155e506882399846ec31cd1403eb05a2abc978718

Observation d77bdbb5-c168-4fcc-8e06-04e285eaf435 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Complex Physics-Informed Neural Network KAN: Kolmogorov-Arnold Networks

Reference 36

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no resolver link, observed 2026-08-08T21:06:33.462633Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T21:06:33.462633Z digest=sha256:e7c6a47d48d83a434e3180b390fd06607b47233c9185cf2168f4fd469ffb2ba9

Observation a5a032d9-18fa-40bf-8ba4-edb37430191a · outbound

This paper cites A comprehen- sive and fair comparison between MLP and KAN representations for differential equations and operator networks.

Complex Physics-Informed Neural Network A comprehen- sive and fair comparison between MLP and KAN representations for differential equations and operator networks

Reference 37

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source=pdf_text observed=2026-08-08T21:06:33.467279Z digest=sha256:a737dc98102905719cb94e9b08381724f886caa665ce2a66513d6430f62ef6aa

Observation 86e6bea7-3ad3-4e4d-a5fb-ce15d1be2f2d · outbound

This paper cites an unresolved cited work.

Complex Physics-Informed Neural Network Unresolved cited work

Reference 38

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raw_fallback, observed 2026-08-08T21:06:33.872555Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.473153Z digest=sha256:f5fd9ec781c6a3e0add09108b4f249c1f11a6f20ded1173153f2a5c1460a2635

Observation c05a34e5-cd89-4d88-a02f-21ebb888f9b7 · outbound

This paper cites PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks.

Complex Physics-Informed Neural Network PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 39

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no resolver link, observed 2026-08-08T21:06:33.477351Z

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source=pdf_text observed=2026-08-08T21:06:33.477351Z digest=sha256:fdb97a275cf12c086632c4bb18599c2eef454c8b2f4aa94cb48eee602b7031fe

Observation b21d2ef1-4302-46a6-a10f-459c25cacebc · outbound

This paper cites Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear partial differential equations.

Complex Physics-Informed Neural Network Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear partial differential equations

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.858480Z

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source=pdf_text observed=2026-08-08T21:06:33.484483Z digest=sha256:56f2239b84e3bee07565e6992b30a7729390cb107d8249fd6b9547bc0e3b4af9

Observation 1d9c2ad6-b45e-4365-bb0a-1ade6a55d8a9 · outbound

This paper cites Binary structured physics-informed neural networks for solving equations with rapidly changing solutions.

Complex Physics-Informed Neural Network Binary structured physics-informed neural networks for solving equations with rapidly changing solutions

Reference 41

Resolution
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local_arxiv, observed 2026-08-08T21:06:33.618170Z

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source=pdf_text observed=2026-08-08T21:06:33.491361Z digest=sha256:27588c59bfafd2ed3a9d56615f39c565091df8bd98ffb799862df3a19b6b32ee

Observation 2c2270df-9af4-4590-8702-f9cb40f7aa32 · outbound

This paper cites f-PICNN: A physics-informed convolutional neural network for partial differential equations with space-time domain.

Complex Physics-Informed Neural Network f-PICNN: A physics-informed convolutional neural network for partial differential equations with space-time domain

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.844502Z

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source=pdf_text observed=2026-08-08T21:06:33.495866Z digest=sha256:516acd606cfd14ffdb0a3726334ad656a06d6da369b8818adbe0f79fbc6efb24

Observation 33a2342c-bb96-4b0d-a2f0-74367b2c5ef9 · outbound

This paper cites Piratenets: Physics-informed deep learning with residual adaptive networks.

Complex Physics-Informed Neural Network Piratenets: Physics-informed deep learning with residual adaptive networks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.830555Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.500802Z digest=sha256:a4d0760fa77956256f67cb6ed8a771337dc25994d86b64725a42dc5711eacb12

Observation 1bccb202-df2a-4b05-b8b0-7367286538e5 · outbound

This paper cites Dasa-pinns: Differentiable adversarial self-adaptive pointwise weighting scheme for physics-informed neural networks.

Complex Physics-Informed Neural Network Dasa-pinns: Differentiable adversarial self-adaptive pointwise weighting scheme for physics-informed neural networks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.815372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.505932Z digest=sha256:f9c1696c7ab0bbf15c7397a570fd6dafdb437530d170518fd74ac1aed2093d29

Observation d63eea75-5ed0-4828-9d93-6b286e342ef6 · outbound

This paper cites Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology.

Complex Physics-Informed Neural Network Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.800100Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.510414Z digest=sha256:627b3ab4b7907bc113b041287f384170be070107083c75a8f80a245b1dc09fa0

Observation 6385ec57-1e70-4870-9ad1-ad5526cf2327 · outbound

This paper cites Residual- based attention in physics-informed neural networks.

Complex Physics-Informed Neural Network Residual- based attention in physics-informed neural networks

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.783936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.514941Z digest=sha256:71fad7e9f9ea2bdb41be93283cdef122f7ea6c23aec3a156334eadede3ccb25f

Observation 8d6e5a09-8104-41c5-abd9-b5c5d496cc7c · outbound

This paper cites Cauchy activation function and XNet.

Complex Physics-Informed Neural Network Cauchy activation function and XNet

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.766010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.519222Z digest=sha256:642c16410b8b1cac597ddb24c7d98a762a7e7dec71b610181e49dba4383daa8b

Observation a39db935-e25d-4637-98a6-5a80d070fb5a · outbound

This paper cites Model Comparisons: XNet Outperforms KAN.

Complex Physics-Informed Neural Network Model Comparisons: XNet Outperforms KAN

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-08T21:06:33.593331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.523390Z digest=sha256:a1c4c757803c6092f792588443fd023780d9ddc845f3076bba39c8d02bf7573c

Observation fc35a959-1c84-4e6a-80f1-8c35a6a7f63a · outbound

This paper cites Wavelets based physics informed neural networks to solve non-linear differential equations.

Complex Physics-Informed Neural Network Wavelets based physics informed neural networks to solve non-linear differential equations

Reference 49

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.528132Z digest=sha256:f69793f650698c8ca3e9394e34667aa8112ca51703f9350f9d1c8623dae549d3

Observation 4ec41083-c49d-465b-b984-c27a8ceb6b22 · outbound

This paper cites The exponentially convergent trapezoidal rule.

Complex Physics-Informed Neural Network The exponentially convergent trapezoidal rule

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.729932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.532486Z digest=sha256:476435be6bccd6dce84da06745bec92521b33261704941450867ba4666df22ed

Observation 99c361fb-5e7a-4e9a-85bf-25f1f567bfb8 · outbound

This paper cites Varieties of sums of powers.

Complex Physics-Informed Neural Network Varieties of sums of powers

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.711035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T21:06:33.537310Z digest=sha256:2ae9a3c4142047feb797bf92512599288edc9059d189aa4bb666b3490bdc7715

Observation 1fc169a6-4e03-4fab-a95d-64332b36dcd5 · outbound

This paper cites Enhanced physics-informed neural networks with augmented lagrangian relaxation method (AL-PINNs).

Complex Physics-Informed Neural Network Enhanced physics-informed neural networks with augmented lagrangian relaxation method (AL-PINNs)

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:06:33.689917Z

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source=pdf_text observed=2026-08-08T21:06:33.543190Z digest=sha256:8b4cc1fda1b60ff8776cd6a640744dae51f8cb4294db03ce20f16868d42e7cb2

Pith citing papers

Observation 7b6a545a-6fa5-4c61-afb7-9ab780877ef2 · inbound

Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks cites this paper.

Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks Complex Physics-Informed Neural Network

Reference 19

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local_arxiv, observed 2026-08-05T15:51:30.187615Z

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source=pdf_text observed=2026-08-05T15:51:29.999525Z digest=sha256:e4a6492529bd1fda9ec208f623a0ee54eb4c7ea10174b30afe470b4c8b10e0ee

Observation ff678914-3106-4921-b877-148fe4c6b682 · inbound

Alternating Levenberg-Marquardt Training of Physics-Informed Neural Networks with Fourier-Enhanced Features cites this paper.

Alternating Levenberg-Marquardt Training of Physics-Informed Neural Networks with Fourier-Enhanced Features Complex Physics-Informed Neural Network

Reference 40

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source=pdf_text observed=2026-08-07T21:41:24.537783Z digest=sha256:210403c3130339de1f57af5021dec7ed45c031b5c7d126bc775e72a730ae7513