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Cited By

G2Φnet: Relating Genotype and Biomechanical Phenotype of Tissues
with Deep Learning

G2Φnet: Relating Genotype and Biomechanical Phenotype of Tissues with Deep Learning

21 August 2022

George Karniadakis

ArXiv (abs)PDF HTML

Papers citing "G2Φnet: Relating Genotype and Biomechanical Phenotype of Tissues with Deep Learning"

4 / 4 papers shown

Physics-Informed Machine Learning in Biomedical Science and Engineering

Physics-Informed Machine Learning in Biomedical Science and Engineering

George Karniadakis

179

1

0

06 Oct 2025

Mechanical Characterization and Inverse Design of Stochastic Architected
Metamaterials Using Neural Operators

Mechanical Characterization and Inverse Design of Stochastic Architected Metamaterials Using Neural Operators

Sridhar Krishnaswamy

George Karniadakis

Horacio D. Espinosa

302

7

0

23 Nov 2023

A Generative Modeling Framework for Inferring Families of Biomechanical
Constitutive Laws in Data-Sparse Regimes

A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse RegimesJournal of the mechanics and physics of solids (JMPS), 2023

George Karniadakis

SyDa MedIm AI4CE

254

12

0

04 May 2023

Recent Advances and Applications of Machine Learning in Experimental
Solid Mechanics: A Review

Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A ReviewApplied Mechanics Review (AMR), 2023

466

102

0

14 Mar 2023

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