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Reproducing kernel particle methods
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Non-linear version of stabilized conforming nodal integration for Galerkin mesh-free methods
Chen, Jiun-Shyan; Yoon, Sangpil; Wu, Cheng-Tang
International Journal for Numerical Methods in Engineering, Vol. 53, Issue 12
https://doi.org/10.1002/nme.338
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Data-driven computing in dynamics: Data-driven computing in dynamics
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Data-Driven Problems in Elasticity
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What-You-Prescribe-Is-What-You-Get orthotropic hyperelasticity
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A topology optimization method for geometrically nonlinear structures with meshless analysis and independent density field interpolation
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Model-free data-driven methods in mechanics: material data identification and solvers
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A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity
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A survey of parametrized variational principles and applications to computational mechanics
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A multilevel finite element method (FE2) to describe the response of highly non-linear structures using generalized continua
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Artificial neural network as an incremental non-linear constitutive model for a finite element code
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Reproducing Kernel Particle Methods for large deformation analysis of non-linear structures
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Multiscale FE2 elastoviscoplastic analysis of composite structures
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Diffusion nets
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Artificial Neural Networks in numerical modelling of composites
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Data-driven computational mechanics
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Data Driven Computing with noisy material data sets
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A new reliability-based data-driven approach for noisy experimental data with physical constraints
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Data-based derivation of material response
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A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning
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A deep material network for multiscale topology learning and accelerated nonlinear modeling of heterogeneous materials
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An unsupervised data completion method for physically-based data-driven models
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Model-Free Data-Driven inelasticity
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A physics-constrained data-driven approach based on locally convex reconstruction for noisy database
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SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials
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Variational framework for distance-minimizing method in data-driven computational mechanics
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Model-free data-driven computational mechanics enhanced by tensor voting
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Neural network constitutive model for rate-dependent materials
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A data-driven approach to nonlinear elasticity
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Finite element analysis of V-ribbed belts using neural network based hyperelastic material model
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An investigation of the anisotropic mechanical properties and anatomical structure of porcine atrioventricular heart valves
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Neural network based constitutive modeling of nonlinear viscoplastic structural response
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Physics-constrained local convexity data-driven modeling of anisotropic nonlinear elastic solids
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Knowledge‐Based Modeling of Material Behavior with Neural Networks
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Deep learning predicts path-dependent plasticity
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Reducing the Dimensionality of Data with Neural Networks
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A Global Geometric Framework for Nonlinear Dimensionality Reduction
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Nonlinear Dimensionality Reduction by Locally Linear Embedding
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Extracting and composing robust features with denoising autoencoders
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January 2008
A two-dimensional interpolation function for irregularly-spaced data
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January 1968
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
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Nonlinear Component Analysis as a Kernel Eigenvalue Problem
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Learning Deep Architectures for AI
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A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics
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