activity
20202025
most citedPrediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

physics.ao-ph2025

A multiresolution weather dataset for the Southwestern South Atlantic (2017-2018)

Luan C. V. Silva, Lívia Sancho, Mauricio S. Silva +19

The Southwestern South Atlantic (SWSA) is a key region for climate research and renewable energy assessment, yet high-resolution meteorological data are scarce. We present a multir…

cs.CE2025

Hybrid DeepONet Surrogates for Multiphase Flow in Porous Media

Ezequiel S. Santos, Gabriel F. Barros, Amanda C. N. Oliveira +6

The solution of partial differential equations (PDEs) plays a central role in numerous applications in science and engineering, particularly those involving multiphase flow in poro…

stat.ML20211 cited

Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning

Rodolfo S. M. Freitas, Ágatha P. F. Lima, Cheng Chen +3

Accurate determination of fuel properties of complex mixtures over a wide range of pressure and temperature conditions is essential to utilizing alternative fuels. The present work…

physics.comp-ph2020

An encoder-decoder deep surrogate for reverse time migration in seismic imaging under uncertainty

Rodolfo S. M. Freitas, Carlos H. S. Barbosa, Gabriel M. Guerra +2

Seismic imaging faces challenges due to the presence of several uncertainty sources. Uncertainties exist in data measurements, source positioning, and subsurface geophysical proper…

eess.SP2020

Digital twin, physics-based model, and machine learning applied to damage detection in structures

TG Ritto, FA Rochinha

This work is interested in digital twins, and the development of a simplified framework for them, in the context of dynamical systems. Digital twin is an ingenious concept that hel…

physics.geo-ph2020

A workflow for seismic imaging with quantified uncertainty

Carlos H. S. Barbosa, Liliane N. O. Kunstmann, Rômulo M. Silva +6

The interpretation of seismic images faces challenges due to the presence of several uncertainty sources. Uncertainties exist in data measurements, source positioning, and subsurfa…