| A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network RG Nascimento, K Fricke, FAC Viana Engineering Applications of Artificial Intelligence 96, 103996, 2020 | 95 | 2020 |
| Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana Journal of Power Sources 513, 230526, 2021 | 86 | 2021 |
| Fleet prognosis with physics-informed recurrent neural networks RG Nascimento, FAC Viana arXiv preprint arXiv:1901.05512, 2019 | 61 | 2019 |
| Estimating model inadequacy in ordinary differential equations with physics-informed neural networks FAC Viana, RG Nascimento, A Dourado, YA Yucesan Computers & Structures 245, 106458, 2021 | 56 | 2021 |
| Cumulative damage modeling with recurrent neural networks RG Nascimento, FAC Viana AIAA Journal 58 (12), 5459-5471, 2020 | 38 | 2020 |
| Physics-informed neural networks package FAC Viana, RG Nascimento, Y Yucesan, A Dourado Zenodo. Retrieved from, 2019 | 14 | 2019 |
| Satellite image classification and segmentation with transfer learning R Giorgiani do Nascimento, F Viana AIAA Scitech 2020 Forum, 1864, 2020 | 12 | 2020 |
| Quadcopter control optimization through machine learning R Giorgiani do Nascimento, K Fricke, F Viana AIAA Scitech 2020 Forum, 1148, 2020 | 11 | 2020 |
| Integrated development environment for analytic authoring AK Subramaniyan, A Iankoulski, RG Do Nascimento US Patent 10,296,296, 2019 | 9 | 2019 |
| A framework for Li-ion battery prognosis based on hybrid Bayesian physics-informed neural networks RG Nascimento, FAC Viana, M Corbetta, CS Kulkarni Scientific Reports 13 (1), 13856, 2023 | 7 | 2023 |
| Quadcopter soft vertical landing control with hybrid physics-informed machine learning K Fricke, R Giorgiani do Nascimento, F Viana AIAA Scitech 2021 Forum, 1018, 2021 | 7 | 2021 |
| System architecture for secure and rapid development, deployment and management of analytics and software systems AK Subramaniyan, J Lazos, NC KUMAR, A Iankoulski, ... US Patent 10,481,874, 2019 | 7 | 2019 |
| Li-ion battery aging with hybrid physics-informed neural networks and fleet-wide data RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana Annual Conference of the PHM Society 13 (1), 2021 | 5 | 2021 |
| Usage-based lifing of lithium-ion battery with hybrid physics-informed neural networks R Giorgiani do Nascimento, F Viana, M Corbetta, CS Kulkarni AIAA AVIATION 2021 FORUM, 3046, 2021 | 5 | 2021 |
| Self-aware and self-registering software and analytics platform components AK Subramaniyan, A Iankoulski, RG Do Nascimento US Patent 10,459,774, 2019 | 5 | 2019 |
| Systems and methods for optimizing graphics processing for rapid large data visualization AK Subramaniyan, AN Iankoulski, RG do Nascimento US Patent 9,978,114, 2018 | 3 | 2018 |
| Quantifying uncertainty in Li-ion battery aging due to unknown usage with hybrid physics-informed neural networks R Giorgiani do Nascimento, F Viana, M Corbetta, CS Kulkarni AIAA SCITECH 2023 Forum, 0536, 2023 | 2 | 2023 |
| Lithium-ion battery prognosis with variational hybrid physics-informed neural networks RG Nascimento University of Central Florida, 2022 | 2 | 2022 |
| Python Implementation of Ordinary Differential Equations Solvers using Hybrid Physics-informed Neural Networks K Fricke, RG Nascimento, FAC Viana Zenodo, 2020 | 2 | 2020 |
| Visualizing corrosion in automobiles using generative adversarial networks A Von Zuben, R Nascimento, F Viana Annual Conference of the PHM Society 12 (1), 9-9, 2020 | 1 | 2020 |
Felipe A. C. VianaHead of Applied ResearchZweryfikowany adres z articul8.ai
