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Paper Citation Record · LEDGER

Constitutive Manifold Neural Networks

As of 13 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.13648.

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pith.paper-citation-record.v1
2506.13648 v3

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measured 48 of 48 reference resolution

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measured 48 of 48 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

48 of 48 outbound references displayed

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Outbound references

Observation fd679056-8ac5-4b33-a8a0-08a4b19e1ded · outbound

This paper cites Field-scale apparent soil electrical conductivity,.

Constitutive Manifold Neural Networks Field-scale apparent soil electrical conductivity,

Reference 1

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Observation 2af50af1-cdb2-44e3-823a-9209d0560ac8 · outbound

This paper cites Stochastic Finite Element Analysis Framework for Mod- elling Mechanical Properties of Particulate Modified Polymer Composites,.

Constitutive Manifold Neural Networks Stochastic Finite Element Analysis Framework for Mod- elling Mechanical Properties of Particulate Modified Polymer Composites,

Reference 2

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Observation ea46d6ed-d401-4d98-b68f-750d0321f10b · outbound

This paper cites A principled approach to conductivity uncertainty analysis in electric field calculations,.

Constitutive Manifold Neural Networks A principled approach to conductivity uncertainty analysis in electric field calculations,

Reference 3

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Observation 64d8ed83-bb74-4638-a097-935130514d06 · outbound

This paper cites An Introduction to Tensors for Students of Physics and Engineering,.

Constitutive Manifold Neural Networks An Introduction to Tensors for Students of Physics and Engineering,

Reference 4

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Observation 67e53e0d-9afd-4f1a-b3b5-9b89ce44fd5d · outbound

This paper cites A review on lightweight materials for defence applications: Present and future de- velopments,.

Constitutive Manifold Neural Networks A review on lightweight materials for defence applications: Present and future de- velopments,

Reference 5

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Observation 45bf7871-12d3-488c-ad76-d981296f14f6 · outbound

This paper cites Electrical Properties Tomogra- phy: A Methodological Review,.

Constitutive Manifold Neural Networks Electrical Properties Tomogra- phy: A Methodological Review,

Reference 6

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Observation 8c79a76d-988a-4fb5-9ed6-6bfc63881e98 · outbound

This paper cites Digital mapping of GlobalSoilMap soil properties at a broad scale: A review,.

Constitutive Manifold Neural Networks Digital mapping of GlobalSoilMap soil properties at a broad scale: A review,

Reference 7

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Observation 1e962201-a2bb-4238-8b4e-d99d61391c76 · outbound

This paper cites Itskov, Tensor Algebra and Tensor Analysis for Engineers: With Applications to Continuum Mechanics.

Constitutive Manifold Neural Networks Itskov, Tensor Algebra and Tensor Analysis for Engineers: With Applications to Continuum Mechanics

Reference 8

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Observation 4846454a-c121-4caa-bf25-bcc2d1af84f8 · outbound

This paper cites Modeling variability of the electrical conduc- tivity tensor for the induction welding of composites,.

Constitutive Manifold Neural Networks Modeling variability of the electrical conduc- tivity tensor for the induction welding of composites,

Reference 9

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This paper cites Stochastic modelling of symmetric positive definite material tensors,.

Constitutive Manifold Neural Networks Stochastic modelling of symmetric positive definite material tensors,

Reference 10

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Observation d6eb8558-9b3d-45b4-a56b-fd8959169167 · outbound

This paper cites Modern Monte Carlo methods for efficient uncertainty quantification and propaga- tion: A survey,.

Constitutive Manifold Neural Networks Modern Monte Carlo methods for efficient uncertainty quantification and propaga- tion: A survey,

Reference 11

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This paper cites Lataniotis, Data-driven uncertainty quantification for high-dimensional engineering problems.

Constitutive Manifold Neural Networks Lataniotis, Data-driven uncertainty quantification for high-dimensional engineering problems

Reference 12

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This paper cites A comparison between (quasi-)Monte Carlo and cubature rule based methods for solving high-dimensional integration problems,.

Constitutive Manifold Neural Networks A comparison between (quasi-)Monte Carlo and cubature rule based methods for solving high-dimensional integration problems,

Reference 13

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This paper cites Kriging, Polynomial Chaos Expansion, and Low-Rank Approximations in Material Science and Big Data Analytics,.

Constitutive Manifold Neural Networks Kriging, Polynomial Chaos Expansion, and Low-Rank Approximations in Material Science and Big Data Analytics,

Reference 14

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This paper cites Surrogate models for uncertainty quantification: An overview,.

Constitutive Manifold Neural Networks Surrogate models for uncertainty quantification: An overview,

Reference 15

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This paper cites Solving multiphysics-based inverse prob- lems with learned surrogates and constraints,.

Constitutive Manifold Neural Networks Solving multiphysics-based inverse prob- lems with learned surrogates and constraints,

Reference 16

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Constitutive Manifold Neural Networks A review of uncertainty quan- tification in deep learning: Techniques, applications and challenges,

Reference 17

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Constitutive Manifold Neural Networks Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification,

Reference 18

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This paper cites Constitu- tive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning,.

Constitutive Manifold Neural Networks Constitu- tive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning,

Reference 19

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Constitutive Manifold Neural Networks Learning constitutive relations using symmetric positive definite neural networks,

Reference 20

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Observation e586c7e1-4d2c-4d3c-845d-9bab1abda3f5 · outbound

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Constitutive Manifold Neural Networks A new family of Constitutive Artificial Neural Networks towards automated model discovery,

Reference 21

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Constitutive Manifold Neural Networks Symmetry-enforcing neural networks with applications to constitutive modeling

Reference 22

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Constitutive Manifold Neural Networks Pennec, P

Reference 23

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Constitutive Manifold Neural Networks A Riemannian Framework for Tensor Computing,

Reference 24

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This paper cites Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder,.

Constitutive Manifold Neural Networks Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder,

Reference 25

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Constitutive Manifold Neural Networks A Riemannian Network for SPD Matrix Learning

Reference 26

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Constitutive Manifold Neural Networks Riemannian batch normalization for SPD neural networks

Reference 27

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Constitutive Manifold Neural Networks Riemannian Residual Neural Networks

Reference 28

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Constitutive Manifold Neural Networks A CNN for homogneous Riemannian manifolds with applications to Neuroimaging

Reference 29

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Constitutive Manifold Neural Networks Anisotropy respecting constitutive neural net- works,

Reference 30

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Constitutive Manifold Neural Networks Reciprocal Relations in Irreversible Processes. I.,

Reference 31

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Constitutive Manifold Neural Networks Smooth Manifolds,

Reference 32

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Constitutive Manifold Neural Networks Gallier and J

Reference 33

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Constitutive Manifold Neural Networks Geometries and Interpolations for Symmetric Positive Definite Matri- ces,

Reference 34

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Constitutive Manifold Neural Networks Unresolved cited work

Reference 35

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Constitutive Manifold Neural Networks A mathematical theory of communication,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:28.894748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 977e7fe0-3d21-4bab-a0f3-85386131d1e0 · outbound

This paper cites Information Theory and Statistical Mechanics,.

Constitutive Manifold Neural Networks Information Theory and Statistical Mechanics,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:28.689407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:23.286519Z digest=sha256:5f6ae9ef896cc2fc034f16742cbc5a1d01c53adb960cf01ed2fbaff31e535c88

Observation 14cc7d6b-cb65-4be1-a1cf-fecfb7ef02af · outbound

This paper cites Geometric Means in a Novel Vector Space Struc- ture on Symmetric Positive-Definite Matrices,.

Constitutive Manifold Neural Networks Geometric Means in a Novel Vector Space Struc- ture on Symmetric Positive-Definite Matrices,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:28.434814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:23.414962Z digest=sha256:f03285d914bdbe0f4b519d8fbf379c3866ceaa7a4ded8d2544d0fff3f399d532

Observation 083013ab-133a-4c62-ad87-0e587671f60d · outbound

This paper cites Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods.

Constitutive Manifold Neural Networks Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:34:26.254829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:23.525560Z digest=sha256:34e4218a994b45b7814fee78440a2e04e4012c510854c067ddbbf40fa55b8891

Observation 90b0e596-3477-4e86-aa87-d4e1915e405c · outbound

This paper cites Riemannian metrics for neural networks I: feedforward networks.

Constitutive Manifold Neural Networks Riemannian metrics for neural networks I: feedforward networks

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T00:34:23.624749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:34:23.624749Z digest=sha256:e8a99ae2ad9d288effd4ac94a589766ce3e0a907b1572f6f0f9d49bd91e13983

Observation 729235f1-9933-4166-b5e8-da6713408bdc · outbound

This paper cites Schwartzman, Random ellipsoids and false discovery rates: statistics for diffusion tensor imaging data.

Constitutive Manifold Neural Networks Schwartzman, Random ellipsoids and false discovery rates: statistics for diffusion tensor imaging data

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:28.277051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:23.896185Z digest=sha256:0c73caf3cd722716f9278cb5439dc2acc1126d2aa3d9c2dd22393eb7aee19516

Observation e47c200b-4875-4596-bf5a-c257ff1adc7f · outbound

This paper cites Lognormal Distributions and Geometric Averages of Symmetric Positive Def- inite Matrices,.

Constitutive Manifold Neural Networks Lognormal Distributions and Geometric Averages of Symmetric Positive Def- inite Matrices,

Reference 42

Resolution
verified exact
doi, observed 2026-08-07T00:34:25.157825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:24.113202Z digest=sha256:e2765e8e618fdab254612279e94e93c3a6987dcc57a68194ad76902905b16859

Observation 167b9b56-8995-4291-b505-0069cc2a1392 · outbound

This paper cites Modeling and experimental in- vestigation of induction welding of thermoplastic composites and comparison with other welding processes,.

Constitutive Manifold Neural Networks Modeling and experimental in- vestigation of induction welding of thermoplastic composites and comparison with other welding processes,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:28.080293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:24.314817Z digest=sha256:a1923897d59d88e71a3f6dc76d351a07314ed08361ff10da13da538ae83fc982

Observation 91651922-407f-416f-9956-2f0f91d1d71f · outbound

This paper cites COMSOL Multiphsyics ® v. 6.2.

Constitutive Manifold Neural Networks COMSOL Multiphsyics ® v. 6.2

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:27.887963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:24.408931Z digest=sha256:90fe6d5f4c649d4ca8b05c79cb9e0169dd0a7f81f4833e6a250cebdc87a402ca

Observation b8b1bd7e-7576-4ef6-8e03-0be29bf69b7d · outbound

This paper cites Optuna: A Next-generation Hyperparameter Optimization Framework.

Constitutive Manifold Neural Networks Optuna: A Next-generation Hyperparameter Optimization Framework

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T00:34:24.568049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:34:24.568049Z digest=sha256:d00b20c829fd118dabee950eb10c493bf0471bf286593d208198ea9dabc97bb1

Observation 8a00b3c0-7a78-4bcd-92eb-f76a30600c06 · outbound

This paper cites Characterisation of Or- thotropic Electrical Conductivity of Unidirectional C/PAEK Thermoplastic Composites,.

Constitutive Manifold Neural Networks Characterisation of Or- thotropic Electrical Conductivity of Unidirectional C/PAEK Thermoplastic Composites,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:27.640926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:24.658258Z digest=sha256:38b1c51dc5302acc38acf8d15ab1c51143dd7404d143b4c6b03f0aca8fa066ac

Observation 97909ca2-a617-463a-8ece-c8f4a3e24906 · outbound

This paper cites Simulating the induction heat- ing of cross-ply C/PEKK laminates – sensitivity and effect of material variability,.

Constitutive Manifold Neural Networks Simulating the induction heat- ing of cross-ply C/PEKK laminates – sensitivity and effect of material variability,

Reference 47

Resolution
verified exact
raw_fallback, observed 2026-08-07T00:34:25.913087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:24.778056Z digest=sha256:c91499127925ea27ebb7c24b5bc6061f600da4828751f3da8712d5131f70cab4

Observation 09c97298-c7d1-44f2-a7ba-a26e1f02b2d3 · outbound

This paper cites Enlighten Project.

Constitutive Manifold Neural Networks Enlighten Project

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:34:27.445875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T00:34:24.924742Z digest=sha256:7e02e9d508a76c35eaad47c81483dab566cffc85d883ccc265aa70960a04c03b

Pith citing papers

No inbound Pith citation observations are available.