Felipe A. C. Viana

Orcid: 0000-0002-2196-7603

Affiliations:
  • University of Central Florida, Orlando, FL, USA


According to our database1, Felipe A. C. Viana authored at least 19 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Physics-informed digital twin for wind turbine main bearing fatigue: Quantifying uncertainty in grease degradation.
Appl. Soft Comput., December, 2024

Guest Editorial: Special Issue on Physics-Informed Machine Learning.
IEEE Trans. Artif. Intell., March, 2024

Steam generator efficiency optimization under uncertainty through multi-fidelity modeling.
J. Comput. Sci., 2024

2023
Anatomically-guided deep learning for left ventricle geometry generation with uncertainty quantification based on short-axis MR images.
Eng. Appl. Artif. Intell., May, 2023

Generative adversarial networks for extrapolation of corrosion in automobile images.
Expert Syst. Appl., 2023

Long Axis Cardiac MRI Segmentation Using Anatomically-Guided UNets and Transfer Learning.
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.
Soft Comput., 2022

2021
Early life failures and services of industrial asset fleets.
Reliab. Eng. Syst. Saf., 2021

Hybrid physics-informed neural networks for main bearing fatigue prognosis with visual grease inspection.
Comput. Ind., 2021

A survey of modeling for prognosis and health management of industrial equipment.
Adv. Eng. Informatics, 2021

A Multi-step Machine Learning Approach for Short Axis MR Images Segmentation.
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.
J. Comput. Inf. Sci. Eng., 2020

A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network.
Eng. Appl. Artif. Intell., 2020

2019
Fleet Prognosis with Physics-informed Recurrent Neural Networks.
CoRR, 2019

2016
A Tutorial on Latin Hypercube Design of Experiments.
Qual. Reliab. Eng. Int., 2016

2013
Efficient global optimization algorithm assisted by multiple surrogate techniques.
J. Glob. Optim., 2013

Lightweight design of vehicle parameters under crashworthiness using conservative surrogates.
Comput. Ind., 2013

2009
Optimization of aircraft structural components by using nature-inspired algorithms and multi-fidelity approximations.
J. Glob. Optim., 2009

2006
Can Ants Design Mechanical Engineering Systems?
Proceedings of the IEEE International Conference on Evolutionary Computation, 2006


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