Paper Citation Record · LEDGER

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams

As of 23 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2501.06925.

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

pith.paper-citation-record.v1
2501.06925 v1

Coverage vector

measured 30 of 30 reference resolution

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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

30 of 30 outbound references displayed

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External citation measurements

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Outbound references

Observation 260f51b6-87ea-4208-bd24-e16e619ccb06 · outbound

This paper cites Beirão da Veiga, F.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Beirão da Veiga, F

Reference 1

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This paper cites Beirão da Veiga, C.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Beirão da Veiga, C

Reference 2

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Observation fa1a7745-66ee-468a-b291-ab48b40ab3dd · outbound

This paper cites Virtual Element Methods for hyperbolic problems on polygonal meshes.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Virtual Element Methods for hyperbolic problems on polygonal meshes

Reference 3

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Observation 36058e7f-ac02-48cb-b60d-83006055123f · outbound

This paper cites Artioli, L.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Artioli, L

Reference 4

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Observation 5fb12ccd-7d51-428d-8a35-07c09cf6cd5c · outbound

This paper cites Wriggers, B.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Wriggers, B

Reference 5

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Observation 1e7caf5d-0baf-4181-b357-8dfa3224c7c8 · outbound

This paper cites A low order 3D virtual element formulation for finite elasto–plastic deformations.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams A low order 3D virtual element formulation for finite elasto–plastic deformations

Reference 6

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Observation df12c701-ae38-4211-a6a9-726275fdf990 · outbound

This paper cites A virtual element method for 3D contact problems with non-conforming meshes.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams A virtual element method for 3D contact problems with non-conforming meshes

Reference 7

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Observation e1af0c9e-0a1e-4882-8b5e-74cc8c5d37e7 · outbound

This paper cites High-order 3D virtual element method for linear and nonlinear elasticity.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams High-order 3D virtual element method for linear and nonlinear elasticity

Reference 8

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This paper cites Wriggers.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Wriggers

Reference 9

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Observation 0d38aa8d-b007-4eed-8f47-349cdbc96673 · outbound

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A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Unresolved cited work

Reference 10

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Observation 4ef3b2bb-edd2-4227-b5fb-cd43d040bc4a · outbound

This paper cites Multilayer feedforward networks are universal ap- proximators.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Multilayer feedforward networks are universal ap- proximators

Reference 11

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Observation dad711bb-11ec-4725-977e-eea02f577320 · outbound

This paper cites Approximation capabilities of multilayer feedforward networks.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Approximation capabilities of multilayer feedforward networks

Reference 12

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Observation 082d0600-2a78-4517-af08-12ff77c1a470 · outbound

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A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Unresolved cited work

Reference 13

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Observation f47024f4-581d-4fce-ace5-401190dd8d64 · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 14

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Observation e3498811-210d-4beb-9d4e-6beb2f3c7270 · outbound

This paper cites Physics Informed Deep Learning (Part II): Data- driven Discovery of Nonlinear Partial Differential Equations.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Physics Informed Deep Learning (Part II): Data- driven Discovery of Nonlinear Partial Differential Equations

Reference 15

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Observation b6b3a974-251c-405d-8fd1-84f7612607c5 · outbound

This paper cites Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: Error analysis and algorithms.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: Error analysis and algorithms

Reference 16

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Observation 5d59a5da-ccad-433a-8cca-f73e8eb68489 · outbound

This paper cites Sharma, L.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Sharma, L

Reference 17

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Observation 9d628d05-4496-4806-91d3-ee8ea19c828c · outbound

This paper cites Jagtap, Shandian Zhe, George Em Karniadakis, and Robert M.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Jagtap, Shandian Zhe, George Em Karniadakis, and Robert M

Reference 18

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Observation 8a836d40-dbd4-4960-ac53-3389e5487f54 · outbound

This paper cites Anagnostopoulos, Juan Diego Toscano, Nikolaos Stergiopulos, and George Em Karniadakis.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Anagnostopoulos, Juan Diego Toscano, Nikolaos Stergiopulos, and George Em Karniadakis

Reference 19

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Observation 76ae8b2d-0930-4ebf-a603-4a5698dc1cf6 · outbound

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

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams When and why PINNs fail to train: A neural tangent kernel perspective

Reference 20

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This paper cites Challenges in Training PINNs: A Loss Landscape Perspective.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Challenges in Training PINNs: A Loss Landscape Perspective

Reference 21

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Observation afa7a1c6-5442-4031-8480-70c94a3d1e74 · outbound

This paper cites Deep learned finite elements.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Deep learned finite elements

Reference 22

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Observation 5ec96b91-794d-4436-b3a8-94ddfd1fbf25 · outbound

This paper cites Self-updated four-node finite element using deep learning.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Self-updated four-node finite element using deep learning

Reference 23

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Observation 20a4fad1-1b88-4c6e-bad0-e2eb260f7495 · outbound

This paper cites A deep energy method for finite deformation hyperelasticity.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams A deep energy method for finite deformation hyperelasticity

Reference 24

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Observation 9e768bd2-a125-4fb4-9efd-d809d9d52aa4 · outbound

This paper cites Abueidda, Seid Koric, Rashid Abu Al-Rub, Corey M.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Abueidda, Seid Koric, Rashid Abu Al-Rub, Corey M

Reference 25

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A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Unresolved cited work

Reference 26

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Observation 51d9aa65-a02a-4fe9-9143-757347e94e66 · outbound

This paper cites Sobolev Training for Neural Networks.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Sobolev Training for Neural Networks

Reference 27

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Observation 536f8601-7f40-481c-ad03-55987aaa25cb · outbound

This paper cites GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks

Reference 28

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Observation ea700b60-b850-4a47-8a16-cea7c3bdb0cf · outbound

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A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams Unresolved cited work

Reference 2013

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Observation 7dd8433c-fa92-4ed9-a925-34da69c50f08 · outbound

This paper cites https://doi.org/10.1016/j.cma.2015.07.013.

A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams https://doi.org/10.1016/j.cma.2015.07.013

Reference 2015

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Pith citing papers

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