3 papers
Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics
Fabio Pereira dos Santos, Renato Portugal, Júlio de Castro Vargas Fernandes +1
Physics-informed neural networks (PINNs) have emerged as a versatile approach for solving nonlinear partial differential equations (PDEs), yet achieving high accuracy efficiently u…
Shearlet Neural Operators for Anisotropic-Shock-Dominated and Multi-scale parametric partial differential equations
Fabio Pereira dos Santos, Julio de Castro Vargas Fernandes, Adriano Mauricio de Almeida Cortes
Neural operators have emerged as powerful data-driven surrogates for learning solution operators of parametric partial differential equations (PDEs). However, widely used Fourier N…
Entropy-based measure of rock sample heterogeneity derived from micro-CT images
Luan Coelho Vieira Silva, Júlio de Castro Vargas Fernandes, Felipe Belilaqua Foldes Guimarães +6
This study presents an automated method for objectively measuring rock heterogeneity via raw X-ray micro-computed tomography (micro-CT) images, thereby addressing the limitations o…