Felipe A. C. Viana

According to our database, Felipe A. C. Viana authored at least 17 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Guest Editorial: Special Issue on Physics-Informed Machine Learning.

Francesco Piccialli, Maizar Raissi, Felipe A. C. Viana, Giancarlo Fortino, Huimin Lu, Amir Hussain

IEEE Trans. Artif. Intell., March, 2024

2023

Anatomically-guided deep learning for left ventricle geometry generation with uncertainty quantification based on short-axis MR images.

Andre Von Zuben, Luigi E. Perotti, Felipe A. C. Viana

Eng. Appl. Artif. Intell., May, 2023

Generative adversarial networks for extrapolation of corrosion in automobile images.

Andre Von Zuben, Felipe A. C. Viana

Expert Syst. Appl., 2023

Long Axis Cardiac MRI Segmentation Using Anatomically-Guided UNets and Transfer Learning.

Andre Von Zuben, Emily Whitt, Felipe A. C. Viana, Luigi E. Perotti

Proceedings of the Functional Imaging and Modeling of the Heart, 2023

2022

Ensemble of hybrid neural networks to compensate for epistemic uncertainties: a case study in system prognosis.

Arinan Dourado, Felipe A. C. Viana

Soft Comput., 2022

2021

Early life failures and services of industrial asset fleets.

Arinan Dourado, Felipe Antonio Chegury Viana

Reliab. Eng. Syst. Saf., 2021

Hybrid physics-informed neural networks for main bearing fatigue prognosis with visual grease inspection.

Yigit A. Yucesan, Felipe Antonio Chegury Viana

Comput. Ind., 2021

A survey of modeling for prognosis and health management of industrial equipment.

Yigit A. Yucesan, Arinan Dourado, Felipe A. C. Viana

Adv. Eng. Informatics, 2021

A Multi-step Machine Learning Approach for Short Axis MR Images Segmentation.

Andre Von Zuben, Kylie Heckman, Felipe A. C. Viana, Luigi E. Perotti

Proceedings of the Functional Imaging and Modeling of the Heart, 2021

2020

Physics-Informed Neural Networks for Missing Physics Estimation in Cumulative Damage Models: A Case Study in Corrosion Fatigue.

Arinan Dourado, Felipe Antonio Chegury Viana

J. Comput. Inf. Sci. Eng., 2020

A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network.

Renato Giorgiani Nascimento, Kajetan Fricke, Felipe Antonio Chegury Viana

Eng. Appl. Artif. Intell., 2020

2019

Fleet Prognosis with Physics-informed Recurrent Neural Networks.

Renato Giorgiani Nascimento, Felipe Antonio Chegury Viana

CoRR, 2019

2016

A Tutorial on Latin Hypercube Design of Experiments.

Felipe Antonio Chegury Viana

Qual. Reliab. Eng. Int., 2016

2013

Efficient global optimization algorithm assisted by multiple surrogate techniques.

Felipe Antonio Chegury Viana, Raphael T. Haftka, Layne T. Watson

J. Glob. Optim., 2013

Lightweight design of vehicle parameters under crashworthiness using conservative surrogates.

Ping Zhu, Feng Pan, Wei Chen, Felipe Antonio Chegury Viana

Comput. Ind., 2013

2009

Optimization of aircraft structural components by using nature-inspired algorithms and multi-fidelity approximations.

Felipe Antonio Chegury Viana, Valder Steffen, Sergio Butkewitsch, Marcus de Freitas Leal

J. Glob. Optim., 2009

2006

Can Ants Design Mechanical Engineering Systems?

Felipe Antonio Chegury Viana, Giovanni Iamin Kotinda, Domingos Alves Rade, Valder Steffen Jr.

Proceedings of the IEEE International Conference on Evolutionary Computation, 2006