OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties
Akshay Joshi, Prakash Thakolkaran, Yiwen Zheng, et al.
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 398, pp. 115225-115225
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

NN-EUCLID: Deep-learning hyperelasticity without stress data
Prakash Thakolkaran, Akshay Joshi, Yiwen Zheng, et al.
Journal of the Mechanics and Physics of Solids (2022) Vol. 169, pp. 105076-105076
Open Access | Times Cited: 98

Automated discovery of generalized standard material models with EUCLID
Moritz Flaschel, Siddhant Kumar, Laura De Lorenzis
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 405, pp. 115867-115867
Open Access | Times Cited: 84

A Review on Data-Driven Constitutive Laws for Solids
Jan N. Fuhg, Govinda Anantha Padmanabha, Nikolaos Bouklas, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 29

Deep learning in computational mechanics: a review
Leon Herrmann, Stefan Kollmannsberger
Computational Mechanics (2024) Vol. 74, Iss. 2, pp. 281-331
Open Access | Times Cited: 28

Automated identification of linear viscoelastic constitutive laws with EUCLID
Enzo Marino, Moritz Flaschel, Siddhant Kumar, et al.
Mechanics of Materials (2023) Vol. 181, pp. 104643-104643
Open Access | Times Cited: 26

Artificial intelligence in metal forming
Jian Cao, Markus� Bambach, Marion Merklein, et al.
CIRP Annals (2024) Vol. 73, Iss. 2, pp. 561-587
Closed Access | Times Cited: 11

Stress Representations for Tensor Basis Neural Networks: Alternative Formulations to Finger–Rivlin–Ericksen
Jan Fuhg, Nikolaos Bouklas, Reese E. Jones
Journal of Computing and Information Science in Engineering (2024) Vol. 24, Iss. 11
Open Access | Times Cited: 10

The language of hyperelastic materials
Georgios Kissas, Siddhartha Mishra, Eleni Chatzi, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 428, pp. 117053-117053
Open Access | Times Cited: 10

Reduced and All-at-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics
Ulrich Römer, Stefan Hartmann, Jendrik‐Alexander Tröger, et al.
Applied Mechanics Reviews (2024), pp. 1-51
Open Access | Times Cited: 9

Uncertainty quantification of 3D acoustic shape sensitivities with generalized nth-order perturbation boundary element methods
Leilei Chen, Ruijin Huo, Haojie Lian, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 433, pp. 117464-117464
Closed Access | Times Cited: 9

Polyconvex neural networks for hyperelastic constitutive models: A rectification approach
Peiyi Chen, Johann Guilleminot
Mechanics Research Communications (2022) Vol. 125, pp. 103993-103993
Open Access | Times Cited: 29

Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID
Moritz Flaschel, Hong Yeon Yu, Nina Reiter, et al.
Journal of the Mechanics and Physics of Solids (2023) Vol. 180, pp. 105404-105404
Open Access | Times Cited: 21

Calibrating constitutive models with full‐field data via physics informed neural networks
Craig M. Hamel, Kevin Long, Sharlotte Kramer
Strain (2022) Vol. 59, Iss. 2
Open Access | Times Cited: 24

Bayesian parameter estimation for the inclusion of uncertainty in progressive damage simulation of composites
Johannes Reiner, Nathaniel J. Linden, Reza Vaziri, et al.
Composite Structures (2023) Vol. 321, pp. 117257-117257
Open Access | Times Cited: 13

Incompressible rubber thermoelasticity: a neural network approach
Martin Zlatić, Marko Čanađija
Computational Mechanics (2023) Vol. 71, Iss. 5, pp. 895-916
Closed Access | Times Cited: 12

Discovering uncertainty: Bayesian constitutive artificial neural networks
Kevin Linka, Gerhard A. Holzapfel, Ellen Kuhl
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4

Discussing the spectrum of physics-enhanced machine learning: a survey on structural mechanics applications
Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa, et al.
Data-Centric Engineering (2024) Vol. 5
Open Access | Times Cited: 4

Discovering non-associated pressure-sensitive plasticity models with EUCLID
Haotian Xu, Moritz Flaschel, Laura De Lorenzis
Advanced Modeling and Simulation in Engineering Sciences (2025) Vol. 12, Iss. 1
Open Access

Learning the physics-consistent material behavior from measurable data via PDE-constrained optimization
Xinxin Wu, Yin Zhang, Sheng Mao
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 437, pp. 117748-117748
Open Access

A generalized theory for physics-augmented neural networks in finite strain thermo-electro-mechanics
Rogelio Ortigosa, Jesús Martínez-Frutos, A. Pérez-Escolar, et al.
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 437, pp. 117741-117741
Closed Access

Deep learning without stress data on the discovery of multi-regional hyperelastic properties
Ruike Shi, Haitian Yang, Jianxu Chen, et al.
Computational Mechanics (2025)
Closed Access

A reparameterization-invariant Bayesian framework for uncertainty estimation and calibration of simple materials
Maximilian P. Wollner, Malte Rolf‐Pissarczyk, Gerhard A. Holzapfel
Computational Mechanics (2025)
Open Access

Stochastic Up-Scaling of Discrete Fine-Scale Models Using Bayesian Updating
Muhammad Sadiq Sarfaraz, Bojana Rosić, Hermann G. Matthies
Computation (2025) Vol. 13, Iss. 3, pp. 68-68
Open Access

Fusion‐Based Constitutive Model (FuCe): Toward Model‐Data Augmentation in Constitutive Modeling
Tushar, Sawan Kumar, Souvik Chakraborty
International journal of mechanical system dynamics (2025)
Open Access

Evaluation of the ability of full-field displacement measurements to extract yield surface parameters
Siamak S. Shishvan, V.S. Deshpande
European Journal of Mechanics - A/Solids (2025), pp. 105652-105652
Open Access

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