Publications

2023

Miranda, E. F., Santos, L. B. L., & Stephany, S. (2023). Data-Driven Parameter Discovery of a One-Dimensional Burgers’ Equation Using a Physics-Informed Neural Network [Manuscript]. DOI: 10.5281/zenodo.10676770 .

2022

Miranda, E. F. (2022). Common MPI-based HPC Approaches in Python Evaluated for Selected Test Cases (Master’s Thesis, National Institute for Space Research - INPE). URI: http://urlib.net/ibi/QABCDSTQQW/46C4U9H .

Miranda, E. F., & Stephany, S. (2022). Common MPI-Based Solutions for High-Performance Processing in Python Evaluated on Selected Test Cases [Presentation]. DOI: 10.5281/zenodo.10676832 .

Miranda, E. F. (2022). Solution of a One-Dimensional Viscous Burgers' Equation Using a Physics-Informed Neural Network and a Gaussian Quadrature Method [Manuscript]. DOI: 10.5281/zenodo.10676900 .

Miranda, E. F. (2022). Comparison of CNN and MLP Artificial Neural Network Models for an Optical Character Recognition Test Case [Manuscript]. DOI: 10.5281/zenodo.10676917 .

2021

Miranda, E. F., & Stephany, S. (2021). Comparison of High-performance Computing Approaches in the Python Environment for a Five-point Stencil Test Problem. XV Brazilian E-Science Workshop, at XLI Congress of the Brazilian Computer Society (CSBC-2021), 33–40. DOI: 10.5753/bresci.2021.15786 .

Miranda, E. F., & Stephany, S. (2021). Common HPC Approaches in Python Evaluated for a Scientific Computing Test Case. Revista Cereus, 13(2), 84–98. DOI: 10.18605/2175-7275/cereus.v13n2p84-98 .

Miranda, E. F., & Stephany, S. (2021). Comparison of high-performance computing approaches in the Python environment for a five-point stencil case study. XV Brazilian e-Science Workshop (BreSci), Online [Presentation]. DOI: 10.5281/zenodo.10672456 .