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Paper Citation Record · LEDGER

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates

As of 14 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.12563.

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

pith.paper-citation-record.v1
2507.12563 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

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measured 35 of 35 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.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 4fb300be-a544-46f5-8e7a-36a6dcdccbb7 · outbound

This paper cites write newline.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates write newline

Reference 1

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This paper cites Efficient synthesis of tension modulation in strings and membranes based on energy estimation.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Efficient synthesis of tension modulation in strings and membranes based on energy estimation

Reference 2

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 3

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 4

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 5

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This paper cites E., and Welling, M.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates E., and Welling, M

Reference 6

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This paper cites L., Brunton, B.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates L., Brunton, B

Reference 7

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Observation 269026b7-3ec7-4f55-bfef-2f9d2de53709 · outbound

This paper cites Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next

Reference 8

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This paper cites and Sandler, M.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates and Sandler, M

Reference 9

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This paper cites Towards Efficient Modelling of String Dynamics : A Comparison of State Space and Koopman based Deep Learning Methods.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Towards Efficient Modelling of String Dynamics : A Comparison of State Space and Koopman based Deep Learning Methods

Reference 10

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 11

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This paper cites Deep learning.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Deep learning

Reference 12

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This paper cites Modeling sequences with structured state spaces.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Modeling sequences with structured state spaces

Reference 13

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Efficiently Modeling Long Sequences with Structured State Spaces

Reference 14

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This paper cites Diagonal State Spaces are as Effective as Structured State Spaces.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Diagonal State Spaces are as Effective as Structured State Spaces

Reference 15

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This paper cites State-space models are accurate and efficient neural operators for dynamical systems.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates State-space models are accurate and efficient neural operators for dynamical systems

Reference 16

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Reference 17

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This paper cites Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation

Reference 18

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 19

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Neural Operator : Learning Maps Between Function Spaces With Applications to PDEs

Reference 20

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 21

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates N., and Brunton, S

Reference 23

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This paper cites Spectrum of the Koopman Operator , Spectral Expansions in Functional Spaces , and State - Space Geometry.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Spectrum of the Koopman Operator , Spectral Expansions in Functional Spaces , and State - Space Geometry

Reference 24

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Koopman Operator , Geometry , and Learning of Dynamical Systems

Reference 25

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates E., and Riemer-Sørensen, S

Reference 26

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates B., Ren, P., Mahoney, M

Reference 28

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates L., Gu, A., Fernando, A., Gulcehre, C., Pascanu, R., and De, S

Reference 29

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Physical Modeling using Recurrent Neural Networks with Fast Convolutional Layers

Reference 30

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 31

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Unresolved cited work

Reference 32

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates and Rabenstein, R

Reference 33

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Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Koopman neural operator as a mesh-free solver of non-linear partial differential equations

Reference 34

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This paper cites Continuous PDE Dynamics Forecasting with Implicit Neural Representations.

Evaluation of Neural Surrogates for Physical Modelling Synthesis of Nonlinear Elastic Plates Continuous PDE Dynamics Forecasting with Implicit Neural Representations

Reference 35

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