John M. Hanna

Inria Saclay - Île de France — France

Physics and Astronomy · Physical Sciences

3h-index137citations11works6.22yr avg
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Research Topics

Model Reduction and Neural Networks(5), Lattice Boltzmann Simulation Studies(4), Injection Molding Process and Properties(2), Non-Destructive Testing Techniques(2), Seismic Imaging and Inversion Techniques(1)

Publications11 total

A comparative analysis of metamodels for 0D cardiovascular models, and pipeline for sensitivity analysis, parameter estimation, and uncertainty quantification
Computers in Biology and Medicine·2025· 3 citedOpen Access
Improved Physics-Informed Neural Networks Loss Function Regularization with a Variance-Based Term
SSRN Electronic Journal·2025Open Access
Improved Physics-informed neural networks loss function regularization with a variance-based term
arXiv (Cornell University)·2024Open Access
A comparative analysis of metamodels for 0D cardiovascular models, and pipeline for sensitivity analysis, parameter estimation, and uncertainty quantification
arXiv (Cornell University)·2024Open Access
Sensitivity analysis using Physics-informed neural networks
Engineering Applications of Artificial Intelligence·2024· 17 cited
A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction
Composites Part A Applied Science and Manufacturing·2024· 17 citedOpen Access
Modélisation de l'écoulement diphasique dans les milieux poreux à l'aide de réseaux neuronaux informés par la physique pour des applications dans le moulage de composites par injection de résine
theses.fr (ABES)·2023Open Access
Sensitivity analysis using Physics-informed neural networks
arXiv (Cornell University)·2023Open Access
Residual-based adaptivity for two-phase flow simulation in porous media using Physics-informed Neural Networks
Computer Methods in Applied Mechanics and Engineering·2022· 100 citedOpen Access
Residual-based adaptivity for two-phase flow simulation in porous media using Physics-informed Neural Networks
arXiv (Cornell University)·2021Open Access
The appeal of a Wesleyan-Arminian, postmodern hermeneutic applied to the practice of Lectio Divina for evangelicals seeking transformational prayer-encounters with God
ePlace - Preserving, Learning, and Creative Exchange (Asbury Theological Seminary)·2008

Frequent Co-authors

Sébastien Comas-Cardona(5), Domenico Borzacchiello(5), Ramzi Askri(4), Irène Vignon-Clémentel(4), José Vicente Aguado(3), José V. Aguado(2), Pavlos Varsos(2), Jérôme Kowalski(2), Lorenzo Sala(2), Roel Meiburg(2), Yves Le Guennec(1), Hugues Talbot(1)