Inverse design of anisotropic microstructures using physics-augmented neural networks | Paper Citation Record

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This paper cites Modeling the anisotropic finite-deformation viscoelastic behavior of soft fiber-reinforced composites.

Inverse design of anisotropic microstructures using physics-augmented neural networks Modeling the anisotropic finite-deformation viscoelastic behavior of soft fiber-reinforced composites

Reference 1

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Inverse design of anisotropic microstructures using physics-augmented neural networks Mechanical properties of anisotropic fiber-reinforced composites

Reference 2

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This paper cites Effects of fiber orientation and anisotropy on tensile strength and elastic modulus of short fiber reinforced polymer composites.

Inverse design of anisotropic microstructures using physics-augmented neural networks Effects of fiber orientation and anisotropy on tensile strength and elastic modulus of short fiber reinforced polymer composites

Reference 3

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Inverse design of anisotropic microstructures using physics-augmented neural networks The anisotropic hooke’s law for cancellous bone and wood

Reference 4

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Inverse design of anisotropic microstructures using physics-augmented neural networks Computational modeling of mechanical anisotropy in the cornea and sclera

Reference 5

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This paper cites Anisotropy properties of tissues: a basis for fabrication of biomimetic anisotropic scaffolds for tissue engineering.

Inverse design of anisotropic microstructures using physics-augmented neural networks Anisotropy properties of tissues: a basis for fabrication of biomimetic anisotropic scaffolds for tissue engineering

Reference 6

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Inverse design of anisotropic microstructures using physics-augmented neural networks Mechanical behavior of materials

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This paper cites Aspects of computational homogenization at finite deformations: a unifying review from reuss’ to voigt’s bound.

Inverse design of anisotropic microstructures using physics-augmented neural networks Aspects of computational homogenization at finite deformations: a unifying review from reuss’ to voigt’s bound

Reference 8

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This paper cites Bickel, Jan Rys, Steve Marschner, Chiara Daraio, and Markus H.

Inverse design of anisotropic microstructures using physics-augmented neural networks Bickel, Jan Rys, Steve Marschner, Chiara Daraio, and Markus H

Reference 9

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This paper cites Mechanical metamaterials and their engineering applications.

Inverse design of anisotropic microstructures using physics-augmented neural networks Mechanical metamaterials and their engineering applications

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This paper cites Anisotropy and heterogeneity of microstructure and mechanical properties in metal additive manufacturing: A critical review.

Inverse design of anisotropic microstructures using physics-augmented neural networks Anisotropy and heterogeneity of microstructure and mechanical properties in metal additive manufacturing: A critical review

Reference 11

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This paper cites Properties of materials: anisotropy, symmetry, structure.

Inverse design of anisotropic microstructures using physics-augmented neural networks Properties of materials: anisotropy, symmetry, structure

Reference 12

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This paper cites Microstructural image analysis applied to fibre composite materials: a review.

Inverse design of anisotropic microstructures using physics-augmented neural networks Microstructural image analysis applied to fibre composite materials: a review

Reference 13

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This paper cites Microstructural imaging techniques: a comparison between light and scanning electron microscopy.

Inverse design of anisotropic microstructures using physics-augmented neural networks Microstructural imaging techniques: a comparison between light and scanning electron microscopy

Reference 14

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This paper cites Multiscale modeling: a review.

Inverse design of anisotropic microstructures using physics-augmented neural networks Multiscale modeling: a review

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This paper cites Principles of multiscale modeling.

Inverse design of anisotropic microstructures using physics-augmented neural networks Principles of multiscale modeling

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This paper cites A numerical two-scale homogenization scheme: the fe2-method.

Inverse design of anisotropic microstructures using physics-augmented neural networks A numerical two-scale homogenization scheme: the fe2-method

Reference 17

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Inverse design of anisotropic microstructures using physics-augmented neural networks Unresolved cited work

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This paper cites A variational approach to the theory of the elastic behaviour of multiphase materials.

Inverse design of anisotropic microstructures using physics-augmented neural networks A variational approach to the theory of the elastic behaviour of multiphase materials

Reference 22

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This paper cites Variational bounds on the effective moduli of anisotropic composites.

Inverse design of anisotropic microstructures using physics-augmented neural networks Variational bounds on the effective moduli of anisotropic composites

Reference 23

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Inverse design of anisotropic microstructures using physics-augmented neural networks Homogenization approach in engineering

Reference 24

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This paper cites The determination of the elastic field of an ellipsoidal inclusion, and related problems.

Inverse design of anisotropic microstructures using physics-augmented neural networks The determination of the elastic field of an ellipsoidal inclusion, and related problems

Reference 25

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Inverse design of anisotropic microstructures using physics-augmented neural networks Average stress in matrix and average elastic energy of materials with misfitting inclusions

Reference 27

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This paper cites Luo and G.J.

Inverse design of anisotropic microstructures using physics-augmented neural networks Luo and G.J

Reference 28

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This paper cites On the elastic moduli of some heterogeneous materials.

Inverse design of anisotropic microstructures using physics-augmented neural networks On the elastic moduli of some heterogeneous materials

Reference 29

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This paper cites On constitutive macro-variables for heterogeneous solids at finite strain.

Inverse design of anisotropic microstructures using physics-augmented neural networks On constitutive macro-variables for heterogeneous solids at finite strain

Reference 31

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This paper cites Geers, V .G.

Inverse design of anisotropic microstructures using physics-augmented neural networks Geers, V .G

Reference 33

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This paper cites Two scale analysis of heterogeneous elastic-plastic materials with asymptotic homogenization and voronoi cell finite element model.

Inverse design of anisotropic microstructures using physics-augmented neural networks Two scale analysis of heterogeneous elastic-plastic materials with asymptotic homogenization and voronoi cell finite element model

Reference 35

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This paper cites Multiscale modeling of microstructure–property relations.

Inverse design of anisotropic microstructures using physics-augmented neural networks Multiscale modeling of microstructure–property relations

Reference 36

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This paper cites Multiscale fe2 elastoviscoplastic analysis of composite structures.

Inverse design of anisotropic microstructures using physics-augmented neural networks Multiscale fe2 elastoviscoplastic analysis of composite structures

Reference 37

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This paper cites A review of the fe 2 method for composites.

Inverse design of anisotropic microstructures using physics-augmented neural networks A review of the fe 2 method for composites

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This paper cites Local approximate gaussian process regression for data- driven constitutive models: development and comparison with neural networks.

Inverse design of anisotropic microstructures using physics-augmented neural networks Local approximate gaussian process regression for data- driven constitutive models: development and comparison with neural networks

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This paper cites A review on data-driven constitutive laws for solids.

Inverse design of anisotropic microstructures using physics-augmented neural networks A review on data-driven constitutive laws for solids

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.150341Z

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This paper cites Representations for isotropic and anisotropic non-polynomial tensor functions.

Inverse design of anisotropic microstructures using physics-augmented neural networks Representations for isotropic and anisotropic non-polynomial tensor functions

Reference 41

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This paper cites A class of orthotropic and transversely isotropic hyperelastic constitutive models based on a polyconvex strain energy function.

Inverse design of anisotropic microstructures using physics-augmented neural networks A class of orthotropic and transversely isotropic hyperelastic constitutive models based on a polyconvex strain energy function

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Inverse design of anisotropic microstructures using physics-augmented neural networks Multilayer feedforward networks are universal approx- imators

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.117806Z

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This paper cites Tensor basis gaussian process models of hyperelastic materials.

Inverse design of anisotropic microstructures using physics-augmented neural networks Tensor basis gaussian process models of hyperelastic materials

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.109515Z

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Observation c677de18-a0c5-4032-91b5-e59dd6f06bbd · outbound

This paper cites On physics-informed data-driven isotropic and anisotropic constitutive mod- els through probabilistic machine learning and space-filling sampling.

Inverse design of anisotropic microstructures using physics-augmented neural networks On physics-informed data-driven isotropic and anisotropic constitutive mod- els through probabilistic machine learning and space-filling sampling

Reference 45

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This paper cites Neural networks meet hyperelasticity: A guide to enforcing physics.

Inverse design of anisotropic microstructures using physics-augmented neural networks Neural networks meet hyperelasticity: A guide to enforcing physics

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.096146Z

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This paper cites Polyconvex anisotropic hyperelasticity with neural networks.

Inverse design of anisotropic microstructures using physics-augmented neural networks Polyconvex anisotropic hyperelasticity with neural networks

Reference 47

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This paper cites Learning hyperelastic anisotropy from data via a tensor basis neural network.

Inverse design of anisotropic microstructures using physics-augmented neural networks Learning hyperelastic anisotropy from data via a tensor basis neural network

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.084121Z

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Observation 62b068dd-4155-4d6d-8226-4e520c6d1606 · outbound

This paper cites A new family of constitutive artificial neural networks towards automated model discovery.

Inverse design of anisotropic microstructures using physics-augmented neural networks A new family of constitutive artificial neural networks towards automated model discovery

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.075754Z

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This paper cites Klein, Fabian J.

Inverse design of anisotropic microstructures using physics-augmented neural networks Klein, Fabian J

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.067050Z

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Observation 11f7121a-053e-4f79-b0cf-40758670cd23 · outbound

This paper cites Non-linear elastic deformations.

Inverse design of anisotropic microstructures using physics-augmented neural networks Non-linear elastic deformations

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.057425Z

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Observation 94e339d0-34f4-4f40-99da-0db8a0e03b73 · outbound

This paper cites Structural tensors for anisotropic solids.

Inverse design of anisotropic microstructures using physics-augmented neural networks Structural tensors for anisotropic solids

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.048264Z

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Observation 26c6335a-2193-453a-986b-f22a5c89bb8c · outbound

This paper cites On the representation of constitutive relations using structure tensors.

Inverse design of anisotropic microstructures using physics-augmented neural networks On the representation of constitutive relations using structure tensors

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.040198Z

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Observation eed8f818-04bb-4e3a-8db4-5822b923c7d5 · outbound

This paper cites Kalina, J ¨org Brummund, WaiChing Sun, and Markus K¨astner.

Inverse design of anisotropic microstructures using physics-augmented neural networks Kalina, J ¨org Brummund, WaiChing Sun, and Markus K¨astner

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.032256Z

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Observation fd6b28f4-af77-470b-9afb-a5381dba6fe4 · outbound

This paper cites An introduction to continuum mechanics , volume 158.

Inverse design of anisotropic microstructures using physics-augmented neural networks An introduction to continuum mechanics , volume 158

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.024122Z

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Observation e7e81b5e-e926-48a6-b5fd-df6227c6d87f · outbound

This paper cites Ordinary and strong ellipticity in the equilibrium theory of incompressible hyper- elastic solids.

Inverse design of anisotropic microstructures using physics-augmented neural networks Ordinary and strong ellipticity in the equilibrium theory of incompressible hyper- elastic solids

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.015694Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a6db226-805f-4117-b3f9-28cddf55c973 · outbound

This paper cites Convexity conditions and existence theorems in nonlinear elasticity.Archive for rational mechanics and Analysis, 63(4):337–403, 1976.

Inverse design of anisotropic microstructures using physics-augmented neural networks Convexity conditions and existence theorems in nonlinear elasticity.Archive for rational mechanics and Analysis, 63(4):337–403, 1976

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.626219Z

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Observation 6b14b3a3-4935-458a-958b-061afdef3a4c · outbound

This paper cites An example of a quasiconvex function that is not polyconvex in two dimensions.

Inverse design of anisotropic microstructures using physics-augmented neural networks An example of a quasiconvex function that is not polyconvex in two dimensions

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:53.003156Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b093cf2-deec-481c-93ea-7c44d0d21f1c · outbound

This paper cites an unresolved cited work.

Inverse design of anisotropic microstructures using physics-augmented neural networks Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-11T13:17:52.995120Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0fe39214-89b9-4370-bdad-bb0b1e489e42 · outbound

This paper cites Boyd and Lieven Vandenberghe.

Inverse design of anisotropic microstructures using physics-augmented neural networks Boyd and Lieven Vandenberghe

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.986913Z

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Observation 89699aa0-8649-4a11-8afb-05e397d3cd41 · outbound

This paper cites Input convex neural networks.

Inverse design of anisotropic microstructures using physics-augmented neural networks Input convex neural networks

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.635749Z

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Observation efb1b4ec-2648-4259-8622-b4958976e2b6 · outbound

This paper cites Mathematical methods in continuum mechanics of solids.

Inverse design of anisotropic microstructures using physics-augmented neural networks Mathematical methods in continuum mechanics of solids

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.974092Z

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Observation 85d3b1d6-1521-487e-88f1-9a09e6435cd7 · outbound

This paper cites Nonlinear solid mechanics: a continuum approach for engineering science.

Inverse design of anisotropic microstructures using physics-augmented neural networks Nonlinear solid mechanics: a continuum approach for engineering science

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.965876Z

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Observation ce72249e-7491-4dbf-a0d5-41c0b4e4c39c · outbound

This paper cites Polyconvexity of generalized polynomial-type hyperelastic strain energy functions for near-incompressibility.

Inverse design of anisotropic microstructures using physics-augmented neural networks Polyconvexity of generalized polynomial-type hyperelastic strain energy functions for near-incompressibility

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.957570Z

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Observation e81501fd-15e8-459d-b5a2-afdd624558bd · outbound

This paper cites Unsupervised discovery of interpretable hyperelastic constitutive laws.

Inverse design of anisotropic microstructures using physics-augmented neural networks Unsupervised discovery of interpretable hyperelastic constitutive laws

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.948238Z

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Observation 136f65c1-6a2e-40c5-904c-71e3d9ff03a2 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Inverse design of anisotropic microstructures using physics-augmented neural networks Pytorch: An imperative style, high-performance deep learning library

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.939910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4966d406-a4f9-4e19-bd27-b1aadb0d2571 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Inverse design of anisotropic microstructures using physics-augmented neural networks Adam: A Method for Stochastic Optimization

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.652954Z

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Observation c04ccc0a-9a0e-4fbc-be7f-27fe67efad30 · outbound

This paper cites A simplex method for function minimization.

Inverse design of anisotropic microstructures using physics-augmented neural networks A simplex method for function minimization

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.656659Z

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This paper cites Implementing the nelder-mead simplex algorithm with adaptive parameters.

Inverse design of anisotropic microstructures using physics-augmented neural networks Implementing the nelder-mead simplex algorithm with adaptive parameters

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.659489Z

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Observation f63bae96-9d6f-4503-ba2e-42c0b1db29c4 · outbound

This paper cites M ¨uller, and Petros Koumoutsakos.

Inverse design of anisotropic microstructures using physics-augmented neural networks M ¨uller, and Petros Koumoutsakos

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.923353Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation acbbfa41-8a51-4307-84f7-b82fe935fd1d · outbound

This paper cites The CMA Evolution Strategy: A Tutorial.

Inverse design of anisotropic microstructures using physics-augmented neural networks The CMA Evolution Strategy: A Tutorial

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.665669Z

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Observation e33dce28-aa92-4dae-b423-6a44144745af · outbound

This paper cites Large sample properties of simulations using latin hypercube sampling.

Inverse design of anisotropic microstructures using physics-augmented neural networks Large sample properties of simulations using latin hypercube sampling

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.668599Z

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Observation 4a7c1ebf-3e69-42b3-8906-d0f223fb60c8 · outbound

This paper cites Mathematical elasticity: Three-dimensional elasticity.

Inverse design of anisotropic microstructures using physics-augmented neural networks Mathematical elasticity: Three-dimensional elasticity

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.911236Z

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Observation f175724d-c1bf-4899-95c4-d82ef721d094 · outbound

This paper cites A simple orthotropic, transversely isotropic hyperelastic constitutive equation for large strain computations.

Inverse design of anisotropic microstructures using physics-augmented neural networks A simple orthotropic, transversely isotropic hyperelastic constitutive equation for large strain computations

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.903390Z

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Observation 071ec043-77fb-4949-8128-26bfcdb8bd95 · outbound

This paper cites A new constitutive framework for arterial wall mechanics and a comparative study of material models.

Inverse design of anisotropic microstructures using physics-augmented neural networks A new constitutive framework for arterial wall mechanics and a comparative study of material models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.895918Z

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Observation 4433db73-b560-45eb-9405-b2f71f3ac6a5 · outbound

This paper cites Model- data-driven constitutive responses: application to a multiscale computational framework.

Inverse design of anisotropic microstructures using physics-augmented neural networks Model- data-driven constitutive responses: application to a multiscale computational framework

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.888187Z

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Observation c365bb22-d86d-4a4d-ae94-679d6bf625cc · outbound

This paper cites Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria.

Inverse design of anisotropic microstructures using physics-augmented neural networks Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.879929Z

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Observation f52c2b83-b054-47ed-83ed-427bcb24dfd8 · outbound

This paper cites an unresolved cited work.

Inverse design of anisotropic microstructures using physics-augmented neural networks Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-11T13:17:52.871625Z

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Observation 6823ab87-60c9-4dfa-86d5-4364e0bd7527 · outbound

This paper cites Ranganathan and Martin Ostoja-Starzewski.

Inverse design of anisotropic microstructures using physics-augmented neural networks Ranganathan and Martin Ostoja-Starzewski

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.864001Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6aa88ae0-0a41-4561-bfd0-f2fe0d10b40e · outbound

This paper cites Homogenization of carbon/polymer composites with anisotropic distribution of particles and stochastic interface defects.

Inverse design of anisotropic microstructures using physics-augmented neural networks Homogenization of carbon/polymer composites with anisotropic distribution of particles and stochastic interface defects

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.855735Z

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Observation cfced910-c418-4851-be0a-c5ba0e834b28 · outbound

This paper cites Vlassis, Puhan Zhao, Ran Ma, Tommy Sewell, and WaiChing Sun.

Inverse design of anisotropic microstructures using physics-augmented neural networks Vlassis, Puhan Zhao, Ran Ma, Tommy Sewell, and WaiChing Sun

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.847230Z

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Observation 55993317-c47c-4297-a376-54347848bebd · outbound

This paper cites Hyperelastic behaviors of closed-cell porous materials at a wide porosity range.

Inverse design of anisotropic microstructures using physics-augmented neural networks Hyperelastic behaviors of closed-cell porous materials at a wide porosity range

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.839057Z

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Observation 2b7111b2-b3d2-46ec-bc5e-b77369c584ed · outbound

This paper cites Mechanical analysis of heterogeneous materials with higher-order parameters.

Inverse design of anisotropic microstructures using physics-augmented neural networks Mechanical analysis of heterogeneous materials with higher-order parameters

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.831017Z

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Observation c2c09d58-85bf-4a84-880b-f950fef073dc · outbound

This paper cites Fe ann: an efficient data-driven multiscale approach based on physics-constrained neural networks and automated data mining.

Inverse design of anisotropic microstructures using physics-augmented neural networks Fe ann: an efficient data-driven multiscale approach based on physics-constrained neural networks and automated data mining

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.823190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 22cfccc0-4f25-44b8-a5b4-8e8e89042f57 · outbound

This paper cites Loss of polyconvexity by homogenization: a new example.

Inverse design of anisotropic microstructures using physics-augmented neural networks Loss of polyconvexity by homogenization: a new example

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.814658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a3715512-1664-43e9-8000-e43bb371e475 · outbound

This paper cites Loss of polyconvexity by homogenization.

Inverse design of anisotropic microstructures using physics-augmented neural networks Loss of polyconvexity by homogenization

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.707933Z

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Observation 47fd40a3-d0e4-46e5-a29e-57d1965b419a · outbound

This paper cites Parameter identification for viscoplastic models based on analytical derivatives of a least-squares functional and stability investigations.

Inverse design of anisotropic microstructures using physics-augmented neural networks Parameter identification for viscoplastic models based on analytical derivatives of a least-squares functional and stability investigations

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.801824Z

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Observation 4fb2a1ea-0d01-4102-84db-cea5b27195ed · outbound

This paper cites Identification of material parameters for constitutive equations.

Inverse design of anisotropic microstructures using physics-augmented neural networks Identification of material parameters for constitutive equations

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.793702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a50b0a3f-7079-4e31-84c3-43f22efa8466 · outbound

This paper cites Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal vari- ables.

Inverse design of anisotropic microstructures using physics-augmented neural networks Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal vari- ables

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.785473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e372aca2-319f-4788-b816-ed23c7aef222 · outbound

This paper cites Automated model discovery of finite strain elastoplasticity from uniaxial experiments.

Inverse design of anisotropic microstructures using physics-augmented neural networks Automated model discovery of finite strain elastoplasticity from uniaxial experiments

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T13:17:52.718308Z

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Observation c0a31151-c780-4795-b671-f4ce8021b0a3 · outbound

This paper cites Fuhg, Asghar Jadoon, Oliver Weeger, D.

Inverse design of anisotropic microstructures using physics-augmented neural networks Fuhg, Asghar Jadoon, Oliver Weeger, D

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.776426Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 27ff4b21-133c-40c7-b37d-dcd11b82bd8d · outbound

This paper cites Russ, Glaucio H.

Inverse design of anisotropic microstructures using physics-augmented neural networks Russ, Glaucio H

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:17:52.767307Z

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